Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed ----12/01/2025 has been entered.
Status of Claims
Claims 1-4 are currently pending and have been examined.
Claims 1 and 2 have been amended.
Claims 1-4 have been rejected.
Claim Interpretation
Claim 1 has been amended to discloses, “wherein the server is physically connected via the network to the medical staff terminal, a database of the server, and the external modules.” There is no description of what the Applicant considers “physically connected” to be.” As such, the Examiner is interpreting it as any tangible connection.
Claim Rejections - 35 USC §112(a)
Claims 1-4 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Original claims may lack written description when the claims define the invention in functional language specifying a desired result but the specification does not sufficiently describe how the function is performed or the result is achieved. For software, this can occur when the algorithm or steps/procedure for performing the computer function are not explained at all or are not explained in sufficient detail (simply restating the function recited in the claim is not necessarily sufficient). In other words, the algorithm or steps/procedure taken to perform the function must be described with sufficient detail so that one of ordinary skill in the art would understand how the inventor intended the function to be performed. See MPEP §§ 2163.02 and 2181, subsection IV. It is not enough that one skilled in the art could write a program to achieve the claimed function, because the specification must explain how the inventor intends to achieve the claimed function to satisfy the written description requirement. See MPEP 2161.01 (citing Vasudevan Software, Inc. v. MicroStrategy, Inc., 782 F.3d 671, 681-683 (Fed. Cir. 2015)).
Claim 1 recites the limitation “a probability calculating unit for… calculating a probabilistic association between the target object and the similar object and calculating a probability regarding the target object using the probabilistic association” and claim 3 discloses, “constructs a probabilistic association between various objects defined for a predetermined patient population with a statistical model, and then calculates the probability regarding the object associated with the target patient”. The Applicant’s specification generally states the following: the probability calculating unit 114 may first construct a probabilistic association between various objects for a particular patient population into a statistical model, and then calculate the probability regarding a target patient using the statistical model. Specifically, the probability calculating unit 114 may construct a probabilistic association between various objects defined for a predetermined patient population into a statistical model, and then calculate the probability regarding an object associated with a target patient. (Applicant’s Specification Page 7, lines 11-17). However, the specification lacks sufficient support in the disclosure for what computer components and algorithm (e.g., the necessary steps and/or flowcharts) that perform the claimed functions, specifically any details of the statistical model or how it calculates a probability regarding the target object nor how the probability is connected to the probabilistic association, in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor possessed the claimed subject matter at the time of filing.
Claims 2 and 4 are rejected as dependent on a rejected base claim.
Further, claim 1 is now amended to read the following limitations that do not have proper support in the specification of the instant application:
A personalized medical tool of a patient
While the specification discloses the external module may be implemented as a medical tool or a personalization tool, there is no disclosure of a personalized medical tool of a patient. As such, the Examiner is interpreting the limitation as a medical tool.
“the electronic medical record server updates attributes of the objects, stores the updated attributes in the database of the server, transmits the updated objects to the medical staff terminal via a network and transmits or receives a control signal or patient physiological data to or from the external modules,… wherein, when updating the attributes of the objects, the electronic medical record server performs the update by modifying a stored object structure referenced by the statement script and by recalculating embedding vectors and probabilistic associations corresponding to the modified attributes without reconstructing unrelated objects, thereby utilizing previously constructed embedding vectors and probabilistic associations to reduce redundant database access and thereby improving processing efficiency of the electronic medical record server by reducing data retrieval latency and redundant computation.”
There is no disclosure in the specification of the above amendments which disclose, to paraphrase, updating attributes, storing updated attributes, transmitting updated objects, transmitting or receiving a control signal or physiological data to or from external modules, or modifying a stored object structure referenced by the statement script and by recalculating embedding vectors and probabilistic associations corresponding to the modified attributes without reconstructing unrelated objects, thereby utilizing previously constructed embedding vectors and probabilistic associations to reduce redundant database access and thereby improving processing efficiency of the electronic medical record server by reducing data retrieval latency and redundant computation.
The specification merely recites retrieving updates of a patient from the code, not updating the attributes of the objects based on the statement script. As such, these limitations disclose new matter and are thus rejected under 112(a).
There is no disclosure in the originally filed claims or the specification of the instant application of modifying a stored object structure referenced by the statement script and by recalculating embedding vectors and probabilistic associations corresponding to the modified attributes without reconstructing unrelated objects, thereby utilizing previously constructed embedding vectors and probabilistic associations. The specification briefly mentions that a medical staff may modify or add dependent commands as needed, however, there is not disclosure of how any previous constructed embedding vectors and probabilistic associations may be used or recalculated. As such, these limitations disclose new matter and are thus rejected under 112(a).
There is no disclosure in the originally filed claims or the specification of the instant application of reducing redundant database access or improving processing efficiency or reducing data retrieval latency and redundant computation. Nor is there disclosure of how the previously presented or amended steps of the claims of the instant application result in the supposed ability to reduce redundant database access, improve the professing efficiency of the electronic medical record, or reduce data retrieval latency and redundant computation. As such, these limitations disclose new matter and are thus rejected under 112(a).
Thus, Claims 1-4 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement.
Claim Rejections - 35 USC § 112(b)
Claims 1-4 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation “the server” in the “objectification unit” limitation, the “command processing unit” limitation as well as in, “wherein the server is physically connected… a database of the server…” There is insufficient antecedent basis for this limitation in the claim. Further, it is unclear if “the server” is the same as “the electronic medical record server” or a different server. The Examiner is interpreting it to be the same server.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-4 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claimed invention is directed to an abstract idea without significantly more. Claims 1-4 are directed to a system, method, or product which are one of the statutory categories of invention. (Step 1: YES).
Independent Claim 1 discloses a programmable electronic medical record system comprising: and an electronic medical record server comprising: an objectification unit expressed in object-oriented programming language from a medical staff terminal communicating with the server, wherein the statement script includes the objects and methods defining operations to be performed on the objects; a command processing unit for processing data according to the objects and the methods of the statement script, wherein a medical-related information and an information about external modules implemented as a personalized medical tool of a patient [and connected to the server via network] are designated as the objects, respectively; an embedding vector unit for converting a unique number and storage information corresponding to a query including the statement script into an N-dimensional embedding vector for each object in the statement script, where the N is a natural number; a probability calculating unit for extracting at least one similar object to a target object using vector similarity between embedding vectors corresponding to the objects, calculating a probabilistic association between the target object and the similar object, and calculating a probability regarding the target object using thedependent command designation unit for defining a command dependent on each object in advance so as to limit a content and a range of a command applicable to each object, wherein the server is physically connected via the network to the medical staff terminal, a database of the server, and the external modules, wherein in response to the processing data according to objects and methods of the statement script, the electronic medical record server updates attributes of the objects, stores the updated attributes in the database of the server, transmits the updated objects to the medical staff terminal via a network and transmits or receives a control signal or patient physiological data to or from the external modules, wherein the command processing unit comprises: a delayed enforcement unit that waits for a completion of a medical result requested within a predetermined period of time and generates an alarm to the medical staff terminal when the predetermined period is exceeded without the completion of the medical result, wherein, when updating the attributes of the objects, the electronic medical record server performs the update by modifying a stored object structure referenced by the statement script and by recalculating embedding vectors and probabilistic associations corresponding to the modified attributes without reconstructing unrelated objects, thereby utilizing previously constructed embedding vectors and probabilistic associations to reduce redundant database access and thereby improving processing efficiency of the electronic medical record server by reducing data retrieval latency and redundant computation.
The examiner is interpreting the above bolded limitations as additional elements as further discussed below. The remaining un-bolded limitations are merely directed to how a medical staff member would organize patient data. The series of steps recited above describe managing personal behavior or relationships or interactions between people and thus are grouped as certain methods of organizing human activity which is an abstract idea.
Further, “calculating a probabilistic association between the target object and the similar object, and calculating a probability regarding the target object using the probabilistic association,” and, “recalculating embedding vectors and probabilistic associations corresponding to the modified attributes,” are directed to a mathematical concept, which is an abstract idea. The abstract ideas are considered together as a single abstract idea for further analysis. (Step 2A- Prong 1: YES. The claims are abstract).
This judicial exception is not integrated into a practical application. Limitations that are not indicative of integration into a practical application include: (1) Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05.f), (2) Adding insignificant extra- solution activity to the judicial exception (MPEP 2106.05.g), (3) Generally linking the use of the judicial exception to a particular technological environment or field of use (MPEP 2106.05.h).
Independent Claim 1 discloses the following additional elements:
An electronic medical record server
An objectification unit
[a script] expressed in object-oriented programming language from a medical staff terminal communicating with the server… [wherein] the server is physically connected via the network to the medical staff terminal, a database of the server, and the external modules
A command processing unit
An embedding vector unit
A probability calculating unit
A dependent command designation unit
A database of the server
Transmits the updated objects to the medical staff terminal via a network
Transmits or receives a control signal or patient physiological data to or from the external modules
A delayed enforcement unit
In particular, the additional elements of the electronic medical record server, objectification unit, [a script] expressed in object-oriented programming language from a medical staff terminal communicating with the [electronic medical record] server… wherein the [electronic medical record] server is physically connected via the network to the medical staff terminal, a database of the server, and the external modules, the command processing unit, embedding vector unit, probability calculating unit, dependent command designation unit, database of the server, and the delayed enforcement unit are recited at a high-level of generality such that it amounts to no more than mere instructions to implement an abstract idea by adding the words ‘apply it’ (or an equivalent) with the judicial exception. Applicant’s specification states - An electronic medical record system 10 of the present invention, as a programmable system, may include an electronic medical record server 100, a medical staff terminal 200, an external module 300, and a wired/wireless network connecting the server and the terminal to each other. (Page 4, lines 11-14).
Additionally, transmitting the updated objects to the medical staff terminal via a network and transmitting or receiving a control signal or patient physiological data to or from the external modules amounts to insignificant extra-solution activity.
These additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Accordingly, claim 1 is directed to an abstract idea(s) without a practical application. (Step 2A-Prong 2: NO: the additional claimed elements are not integrated into a practical application).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of the additional elements of the electronic medical record server, objectification unit, [a script] expressed in object-oriented programming language from a medical staff terminal communicating with the [electronic medical record] server… wherein the [electronic medical record] server is physically connected via the network to the medical staff terminal, a database of the server, and the external modules, the command processing unit, embedding vector unit, probability calculating unit, dependent command designation unit, database of the server, and the delayed enforcement unit amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept ("significantly more’). MPEP2106.05(I)(A) indicates that merely saying "apply it” or equivalent to the abstract idea cannot provide an inventive concept ("significantly more").
Transmitting the updated objects to the medical staff terminal via a network and transmitting or receiving a control signal or patient physiological data to or from the external modules were considered insignificant extra-solution activity in Step 2A, Prong 2. Re-evaluating here in step 2B, these are also determined to be well-understood, routine, and conventional activity in the field.
Further, receiving a control signal or patient physiological data to or from the external modules was considered insignificant extra-solution activity in Step 2A, Prong 2. Re-evaluating here in step 2B, these are also determined to be well-understood, routine, and conventional activity. The courts have recognized computer function of receiving or transmitting data over a network, e.g., using the internet to gather data as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network). Further, The Mayo and OIP Techs court decisions cited in MPEP 2106.05(g) indicating that mere data gathering is well-understood, routine, and conventional activity in the field.
In regards to the newly added limitation that claims the system “reduce[s] redundant database access and thereby improv[es] processing efficiency of the electronic medical record server by reducing data retrieval latency and redundant computation.” As presented above, there is no support for this limitation nor any explanation how the features of the claim nor the features described in the specification provide the claimed “improvements.” See MPEP 2106.05(f), “The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words “apply it”. See Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1356, 119 USPQ2d 1739, 1743-44 (Fed. Cir. 2016); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1327, 120 USPQ2d 1353, 1366 (Fed. Cir. 2016); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1417 (Fed. Cir. 2015).” As such, this argument is not persuasive.
Accordingly, independent claim 1 is not patent eligible. (Step 2B: NO. The claims do not provide significantly more).
Dependent claim(s) 2-4 are similarly rejected because they either further define/narrow the abstract idea of claim 1 and/or do not further limit the claim to a practical application or provide an inventive concept such that the claims are subject matter eligible even when considered individually or as an ordered combination.
Dependent claim 3 further discloses, “constructing a probabilistic association between various objects defined for a predetermined patient population with a statistical model, and then calculates the probability regarding the object associated with the target patient” which is similar directed to a mathematical concept as the probabilistic association and probability of claim 1, which is an abstract idea.
Dependent claim 2 does further disclose the additional element of a condition enforcement unit.
The condition enforcement unit is recited at a high-level of generality such that it amounts to no more than mere instructions to implement an abstract idea by adding the words ‘apply it’ (or an equivalent) with the judicial exception. Accordingly, this additional element does not integrate the abstract idea into a practical application.
Also, as discussed above with respect to integration of the abstract idea into a practical application, the additional element of the condition enforcement unit (claim 2) amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept ("significantly more’). MPEP2106.05(I)(A) indicates that merely saying "apply it” or equivalent to the abstract idea cannot provide an inventive concept ("significantly more"). Accordingly, even in combination, these additional element do not provide significantly more.
Therefore, the dependent claims 2-4 are also directed to an abstract idea.
Thus, Claims 1-4 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-3 are rejected under 35 U.S.C. 103 as being unpatentable over Jenders (Arden Syntax Implementation Guide Release 3), in view of Moshfeghi (WO 00/57339), further in view of Barkers (US Patent 6,560,165 B1), Steinberg-Koch (US PG Pub 2022/0223293 A1) and Walters (US PG Pub 2021/0319004A1).
Regarding Claim 1, Jenders discloses:
(Original) A programmable electronic medical record system comprising:
and an electronic medical record servercomprising: an objectification unit for generating one or more objects from a statement script expressed in object-oriented programming language, wherein the statement script includes the objects and methods defining operations to be performed on the objects, a command processing unit for processing data according to the objects and the methods of the statement script, wherein a medical-related information and an information about external modules implemented as a personalized medical tool of a patient and connected to the server via network are designated as the objects, respectively; (Section 8.7 discloses Let PatientIDRecord BE OBJECT [AccountNum, Name, Birthdate, Sex]; LET Patient BE Read As PatientIDRecord Latest {select accountnum, name, dateofbirth, sex from EHR}… LET Medication BE OBJECT [Drug_Name, Form, Dosage, Route, Schedule] [patient information and medication information as medical-related information] ; LET VAQTA BE Read As Medication {select med, form, dose, route, schedule from EHR where med = 'VAQTA'} ; LET HAVRIX BE Read As Medication {select med, form, dose, route, schedule from EHR where med = 'HAVRIX'} ; LET TWINRIX BE Read As Medication {select med, form, dose, route, schedule from EHR where med = 'TWINRIX'} ; [thus disclosing examples of medical related information]. Section 10 discloses LET Observation BE OBJECT (status, code, subject, effective)… LET Latest_HbA1c BE READ AS Observation LATEST [thus disclosing the method of the objects Observation and Latest_HbA1c] WHERE Latest_HbA1c.subject.identifier.value = Current_Patient and Latest_HbA1c.Status = "final" and Latest_HbA1c.Code.Coding.system = "http://loinc.org" and Latest_HbA1c.Coding.code = "55454-3"… evoke: Encounter_Event;; logic: IF Exist(Diabetic_Problem) or Exist(Diabetic_Diagnosis) THEN Diabetes_Present := True; ENDIF; IF Diabetes_Present and exist Latest_HbA1c and Latest_HbA1c Occurred not within past 6 months THEN conclude true; ENDIF; conclude false; ;; action: WRITE "subject is a diabetic with no HbA1c in last 6 months. Please order one."; [thus disclosing HbA1c (information of a personalized medical tool wherein figure 8 discloses the latest HbA1c is retrieved from the FHIR [broadly a personalized medical tool] and thus connected to a server via a network to allow the exchange of medical data) as an object]. 11.3 Examples discloses a simple illustration of this idea is found in Figure 7. It recapitulates the Arden MLM in above, “Rule 1-HbA1c Timing”. The evoking process is represented as a signal event emitted as a part of a care process. The data needed by the MLM is supplied by FHIR-based services and the MLM’s logic is embedded in a business rules task. Fig. 7 discloses one approach to rendering Rule 1-HbA1c Timing as a BPMN-based process. The activities in an EHR are represented by a pool that can send messages and signals and receive messages from processes outside the EHR. This model is triggered by a signal event, “Patient Registration”. The workflow moves in parallel to three service activities, each of which makes a FHIR based call to collect data from the EHR [an external personalized medical tool]. The results of these queries are then available to a business rules task that implements the relevant medical logic and the result is returned to EHR using a terminal message event. Page 71 discloses when using an Arden-Syntax-compliant system, the user is able to create, import, customize, or otherwise implement MLMs without the need for vendor or system developer intervention. Additionally, the user can take an MLM from any institution, alter the content of the curly brace expressions, and make other related adjustments; the resultant MLM will be able to compile and execute at the user’s institution [thus reading on receiving the statement script from a medical staff terminal].)
a dependent command designation unit for defining a command dependent on each object in advance so as to limit a content and a range of a command applicable to each object (Section 10 discloses LET Observation BE OBJECT (status, code, subject, effective)… LET Latest_HbA1c BE READ AS Observation LATEST WHERE Latest_HbA1c.subject.identifier.value = Current_Patient and Latest_HbA1c.Status = "final" and Latest_HbA1c.Code.Coding.system = "http://loinc.org" and Latest_HbA1c.Coding.code = "55454-3”…[Observation is defined as an object and thus this discloses a command dependent on an example object and thus limits the content and range of the command applicable to each object. Observation is treated as the data object that the Read… Latest command is acting upon where the command is dependent on specific properties of that object].)
wherein in response to the processing data according to objects and methods of the statement script, the electronic medical record server updates attributes of the objects, … wherein, when updating the attributes of the objects, the electronic medical record server performs the update by modifying a stored object structure referenced by the statement script (7.1 discloses organizations may encounter the need to connect an Arden-Syntax-based application to an arbitrary electronic health record (EHR) system. As a result, there may be interest in developing applications incorporating standards-based clinical logic representation and accessing EHR data in a schema-independent fashion. 7.2 Sample implementation discloses an Arden Syntax engine equipped with a simple web service interface that is able to receive the identification of an MLM to call and the needed data in simple XML format. Special forms (for each task, e.g., score calculation, parameter check) in the PDMS are defined to collect the necessary data from the user or the internal storage and then sent to the Arden Syntax engine using the web service interface. Returned results from the engine are displayed in the same form. 8.7 discloses Let GenericMessage BE OBJECT [MessageID, MessageCode, Message_Text]; Let Vaccine_Message BE New GenericMessage;… if Apply_young_patient_rules and Not Hepatitis_vaccination then Vaccine_Message.Message_Text := "Give VAQTA vaccine, 25U, IM now and repeat in 6 to 18 months."; Conclude true; endif; [thus disclosing updating the attribute “Message_Text” of the object “Vaccine_Message”] 9.1 discloses the reason that a data model is important in clinical decision support systems is that the system will require access to data in order to apply or process its clinical knowledge. Because a data model may be used as the logical model of how data are stored in a repository that is queried by a decision support system, knowledge of the data model is required to devise the query that is presented by the clinical decision support system (CDSS) to the database management system (DBMS) in order to retrieve the data. Once retrieved, these data are referenced within units of knowledge such as an Arden Syntax MLM within the CDSS.)
and transmits or receives a control signal or patient physiological data to or from the external modules, wherein the command processing unit comprises: (See 11.3 and Figure 7 where Fig. 7 discloses one approach to rendering Rule 1-HbA1c Timing as a BPMN-based process. The activities in an EHR are represented by a pool that can send messages and signals and receive messages from processes outside the EHR. This model is triggered by a signal event, “Patient Registration”. The workflow moves in parallel to three service activities, each of which makes a FHIR based call to collect data from the EHR [wherein the figure shows retrieving latest HbA1c, diabetic problem, and diabetic discharge diagnosis using the FHIR based call to collect data from the EHR]. The results of these queries are then available to a business rules task that implements the relevant medical logic and the result is returned to EHR using a terminal message event. See Further: Figure 8 and Section 10.)
While Jenders discloses the above limitations and Jenders discloses a need to connect and Arden-Syntax-based application to an arbitrary electronic health record (EHR) system and the read statement reads data from external resources and the CDS resource in turn uses standard web services to access a standards-based data layer to fetch data from the target EHR [external module], it does not fully disclose the following limitation that Moshfeghi discloses:
from a medical staff terminal communicating with the server, wherein the server is physically connected via the network to the medical staff terminal, a database of the server, and the external modules (Column 4, lines 11-28 disclose the present invention includes an object-oriented system for computerized patient record (CPR) presentation to a user at an end-user device, the object-oriented system for implementation on computers connected by a network, the system comprising: one or more medical-records-server objects comprising CPR-request methods that input requests for CPR data, access requested data in CPR databases [external modules], and return requested CPR data… Colum 6, lines 19-27 and Fig. 1A disclose that the system infrastructure includes network connected computers functioning primarily (but not necessarily exclusively) either as third tier back-end computers, second-tier server computers, or first-tier end-user computers or devices. Back-end computers, such as computers 10 and 11, are adapted for permanent storage of CPR data. They are advantageously provided with adequate with processing resources, main memory, and storage facilities, such as disk storage 12 which may be magnetic or optical, and with database and application software, either legacy software or software initially designed as object-oriented, for managing attached storage facilities and presenting its contents. Column 7, lines 1-15 discloses the computers and end-user devices of this invention are networked using physical links of various types. Fig. 1A illustrates network 15 providing for general connectivity, such as the public Internet or one or more private intranets implementing the Internet suite of communication protocols including TCP/IP… Column 15, lines 9-16 disclose persistent CPR data of all types, for example those types previously enumerated and other types that may be become useful, are stored on back-end server computer systems, which make the stored data available as data-server objects, such as system 77. Column 17, lines 13-15 discloses rules are stored separately from the business-server objects in rule databases, or rulebases. Needed rules are retrieved from the rulebases by business-server objects or the rules engine as needed. Colum 24, lines 7-14 disclose the rules of this invention, which are separately stored in rule databases and are retrieved by the business-server objects and the rules engine, are advantageously grouped into and retrieved as rule modules [wherein the rule modules are disclosed in Fig. 3 of the middle tier servers thus it is a database of the server], which are collections of rules and rule-sets directed to similar situational analysis.)
stores the updated attributes in the database of the server, transmits the updated objects to the medical staff terminal via a network (Colum 4, lines 11-28 disclose the present invention includes an object-oriented system for computerized patient record (CPR) presentation to a user at an end-user device, the object-oriented system for implementation on computers connected by a network… Column 17, lines 16-26 discloses rule modules also facilitate rule update and maintenance, since each rule module can be maintained by the most knowledgeable person. For, example, administrators can update policy and practice rules; domain experts can update decision support rules; and users can update their personal rules. Columns 17-18 and lines 32-34 and 1-8 discloses rules used in this invention can be programmed with various commercially available knowledge-based application generators, including, inter alia, ART*Enterprise (Brightware), LiveModel (Intellicorp), Elements/Advisor (Neuron Data) and AionDS (Platinum Technology). Each of these have their own specific syntax for specifying rules. Also, the Arden syntax has been developed for general uses in medical knowledge applications, and has been adopted as a standard for health knowledge representation. See, e. g., http://www. cpmc. columbia. edu/resources/arden. A preferable commercial knowledge-based system provides graphic rules editors for defining new rules and modifying existing rules, so that even non-programmers can view and update rules. Such a product also provides tools for checking the consistency of the rules. Colum 24, lines 7-14 disclose the rules of this invention, which are separately stored in rule databases and are retrieved by the business-server objects and the rules engine, are advantageously grouped into and retrieved as rule modules [wherein the rule modules are disclosed in Fig. 3 of the middle tier servers], which are collections of rules and rule-sets directed to similar situational analysis. Column 30, lines 18-24 disclose push technologies can copy an updated rules module to all middle-tier server systems and to all end-user devices to which it has been downloaded.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the Arden Syntax Implementation Guide as taught by Jenders with the rules of the Arden Syntax of the system and method for presentation of computerized patient records across a network as taught by Moshfeghi in order to utilize a standard for health knowledge representation and provide modules of rules to improve performance because only a subset of the rules and object are used at any given time where Arden Syntax allows for the creation of MLMs each representing a single, actionable medical rule to execute health knowledge representation.
While the combination of Jenders and Moshfeghi discloses the above limitations, it does not fully disclose the following limitation that Barker discloses:
a delayed enforcement unit that waits for a completion of a medical result requested within a predetermined period of time and generates an alarm to the medical staff terminal when the predetermined period is exceeded without the completion of the medical result, (Abstract discloses a medical information appliance which reminds a user of times to take medications or to perform medical-related activities. It features a delay mode, which shuts off but later reminds the user to take the indicated medication. Column 2, lines 35-42 discloses it is an object of the invention to provide a medical information appliance in which medical events such as medications or other medical activities can be recorded, and times can be recorded for each medical event. It is a further object to remind a user when the time for performing a medical event arrives, and to provide a way for him to turn the alarm off but still be reminded to perform the activity at a later time. Column 3, lines 33-49 discloses the device also includes a reminder mode activation means, for activating a reminder mode. When the reminder mode is activated, typically by pressing a button, the notification means is deactivated. The notification means would typically be an alarm, a buzzer, or a vibration. When the reminder is activated, after a period of time, a reminder alarm sounds. This would typically be a brief alarm sound, which did not continue, but repeated itself at regular intervals of time until the reminder mode was deactivated. When the reminder mode is activated, the medical event associated with that reminder mode is displayed in the display means. The device also includes a confirmation means, typically a button, which deactivates the reminder mode and which a user activates when the medical event is responded to. This would typically be button which is depressed when the user was able to take the medication indicated by an earlier alarm, and would deactivate the continuing reminder alarm.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of the Arden Syntax Implementation Guide as taught by Jenders and the rules of the Arden Syntax of the system and method for presentation of computerized patient records across a network as taught by Moshfeghi with the medical information appliance as taught by Barker in order to remind a user when the time for performing a medical event arrives and to provide interval alarms that do not stop until completion of the event is recorded so that the user does not forget to perform a medical event.
While the combination of Jenders, Moshfeghi, and Barker discloses the above limitations, the combination does not fully disclose the following limitation that Steinberg-Koch discloses:
a probability calculating unit for extracting at least one similar object to a target object using vector similarity between embedding vectors corresponding to the objects calculating a probability regarding the target object the probabilistic association; and (Para 42-43 discloses generating, using self-supervised representation learning, a feature embedding transformation that converts the input medical history parameters and data into a vector of real numbers in a way that encapsulates a compact representation of data that influences the diagnosis algorithm, such that patients with similar conditions and symptoms will transform into similar vectors… 3) Transforming the selected patient files from step 1 using the feature embedding transform developed in step 2 and combining the output vectors with the target diagnosis to generate a database of training vectors… The classifier maps a patient medical feature vector into a diagnosis probability vector that provides likelihood of a subject having the specified gastrointestinal autoimmune disease. Para 132 discloses the feature embedding model is a machine learning transformation that converts the patient data into a finite vector of real numbers. The vector space is of lower dimension than the entire patient data and therefore compresses the data keeping the important aspects and features that enable subject classification and diagnosis but also makes similar patients convert into vectors with a small distance between them [vector similarity]. This transformation generates a representation of the data that is easier to classify and can better classify new subjects it has not seen before. Para 136 discloses multi-label classification is a classification mechanism that outputs multiple results associated with the likelihood of the inspected object being of a specified class [probabilistic association between the similar object (specified class) and target object (inspected object)]. The classifier classifies object into multiple classes based on the input features of the object. In the context of this disclosure, the classifier [statistical model trained on likelihoods of objects being similar] provides probabilities of the analyzed person having: any autoimmune disease, any gastrointestinal autoimmune disease, or a specific autoimmune disorder based on features found in his collection of medical records and data. Para 160 discloses assigning each individual to a particular group… on the basis of the diagnosis probability vector.)
and by recalculating embedding vectors and probabilistic associations corresponding to the modified attributes without reconstructing unrelated objects, thereby utilizing previously constructed embedding vectors and probabilistic associations to reduce redundant database access and thereby improving processing efficiency of the electronic medical record server by reducing data retrieval latency and redundant computation. (Paras 114-118 discloses wherein the at least one processor is configured to: a) apply the expert medical logic to the health related data to produce updated patient feature vectors and patient diagnosis vectors, b) generate classifier model parameters based on algorithm training to process the feature vectors, c) input the classifier model parameters into an embedding model to classify the patient diagnosis vectors, and d) output the likelihood of a predictive diagnosis of at least one autoimmune disease in the subject. Para 132 discloses the vector space is of lower dimension than the entire patient data and therefore compresses the data keeping the important aspects and features that enable subject classification and diagnosis but also makes similar patients convert into vectors with a small distance between them. This transformation generates a representation of the data that is easier to classify and can better classify new subjects it has not seen before. Para 141 discloses the physician’s analysis of the system’s performance is input to the expert medical logic database of step 102, to update and improve that data. Para 172 discloses thus, the system may be updated on a regular basis to incorporate the current standard of treatment for CD. Thus, the outcomes should continually improve over time.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of the Arden Syntax Implementation Guide as taught by Jenders, the rules of the Arden Syntax of the system and method for presentation of computerized patient records across a network as taught by Moshfeghi and the medical information appliance as taught by Barker with the method of evaluating autoimmune disease risk and treatment selection as taught by Steinberg-Koch in order to generate a feature embedding transformation of the patients medical history (Steinberg-Koch Abstract) and allow for personalized care and treatment selection based on subjects’ clustering and similarities (Steinberg-Koch para 34).
While Steinberg-Koch discloses “the embedding transformation and the multi-label classifier are then applied to a current subjects data to generate a patient diagnosis probability vector, predicting the existence of autoimmune conditions” (Abstract), and, “a feature embedding transformation that converts the input medical history parameters and data into a vector of real numbers in a way that encapsulates a compact representation of data that influences the diagnosis algorithm, such that patients with similar conditions and symptoms will transform into similar vectors. Whereas a vector is a one dimensional array of numbers [where one is a natural number]” (Para 42-43), the combination of Jenders, Barker, and Steinberg-Koch does not fully disclose the following limitation that Walters discloses:
an embedding vector unit for converting a unique number and storage information corresponding to a query including the statement script into an N-dimensional embedding vector for each object in the statement script, where N is a natural number, (Para 4 discloses the processor circuit performs operations comprising one or more of: identify a set of data objects, each data object in the set of data objects comprising a key [unique number] and an object value [storage information corresponding to a query (object value) of the statement script], wherein each object value comprises value data or an embedded object; analyze the set of data objects to determine one or more data characteristics of the set of data objects; determine one or more embedding space parameters based on the one or more data characteristics of the set of data objects, wherein the one or more embedding space parameters define an embedding space comprising a plurality of dimensions, the plurality of dimensions including a key dimension.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of the Arden Syntax Implementation Guide as taught by Jenders, the rules of the Arden Syntax of the system and method for presentation of computerized patient records across a network as taught by Moshfeghi, the medical information appliance as taught by Barker and the method of evaluating autoimmune disease risk and treatment selection as taught by Steinberg-Koch with the techniques for creating and utilizing multidimensional embedding spaces as taught by Walters in order to efficiently and effectively convert data objects into object vectors sets mapped to a multidimensional embedding space customized for the set of data objects (Walters para 15).
Regarding Claim 2, this claim recites the limitations of Claim 1 and as to those limitations is
rejected for the same basis and reasons as disclosed above. The combination of Jenders, Moshfeghi, Barker, Steinberg-Koch, and Walter discloses the following limitation that Jenders further discloses:
The electronic medical record system according to claim 1, wherein the command processing unit further comprises: (10 discloses IF Exist(Diabetic_Problem) or Exist(Diabetic_Diagnosis) THEN Diabetes_Present := True; ENDIF; IF Diabetes_Present and exist Latest_HbA1c and Latest_HbA1c Occurred not within past 6 months THEN conclude true; ENDIF; conclude false; ;; action: WRITE "subject is a diabetic with no HbA1c in last 6 months. Please order one.";; [thus the conclude true and the action is enforcing a predetermined statement if the “IF” statement is satisfied based on the statement script].)
Regarding Claim 3, this claim recites the limitations of Claim 1 and as to those limitations is
rejected for the same basis and reasons as disclosed above. The combination of Jenders, Moshfeghi, Barker, Steinberg-Koch, and Walter discloses the following limitation that Steinberg-Koch further discloses:
The electronic medical system according to claim 1, wherein the probability calculation unit extracts patients with a condition similar to that of a target patient by utilizing a patient object obtained by objectifying patient information and an embedding vector defined in each patient object, and then calculates a probability regarding an object associated with the target patient from statistical information of the patients extracted; or constructs a probabilistic association between various objects defined for a predetermined patient population with a statistical model, and then calculates the probability regarding the object associated with the target patient. (Abstract discloses the embedding transformation and the multi-label classifier are then applied to a current subjects data to generate a patient diagnosis probability vector, predicting the existence of autoimmune conditions. Para 42 discloses a feature embedding transformation that converts the input medical history parameters and data into a vector of real numbers in a way that encapsulates a compact representation of data that influences the diagnosis algorithm, such that patients with similar conditions and symptoms will transform into similar vectors. Para 136 discloses multi-label classification is a classification mechanism that outputs multiple results associated with the likelihood of the inspected object being of a specified class. The classifier classifies object into multiple classes based on the input features of the object. In the context of this disclosure, the classifier provides probabilities of the analyzed person having: any autoimmune disease, any gastrointestinal autoimmune disease, or a specific autoimmune disorder, based on features found in his collection of medical records and data. Para 160 discloses assigning each individual to a particular group… on the basis of the diagnosis probability vector.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the automated dynamic generation of interface sequences for data record creation and methods of use thereof as taught by Legere with the method of evaluating autoimmune disease risk and treatment selection as taught by Steinberg-Koch in order to generate a feature embedding transformation of the patients medical history (Steinberg-Koch Abstract) and allow for personalized care and treatment selection based on subjects’ clustering and similarities (Steinberg-Koch para 34).
Claim(s) 4 is rejected under 35 U.S.C. 103 as being unpatentable over Jenders (Arden Syntax Implementation Guide Release 3), in view of Moshfeghi (WO 00/57339), further in view of Barkers (US Patent 6,560,165 B1), Steinberg-Koch (US PG Pub 2022/0223293 A1) and Walters (US PG Pub 2021/0319004A1), Legere (WO 2021155103 A1), and Chaudhry (US PG Pub 2011/0238446 A1).
Regarding Claim 4, this claim recites the limitations of Claim 1 and as to those limitations is
rejected for the same basis and reasons as disclosed above. While Jenders 8.7 discloses /* text within curly brackets would be replaced with an institution's own query */ Let PatientIDRecord BE OBJECT [AccountNum, Name, Birthdate, Sex]; LET Patient BE Read As PatientIDRecord Latest {select accountnum, name, dateofbirth, sex from EHR} ; LET outpatient_visit BE EVENT {select encounter_type, start_time_stamp, end_time_stamp, attending, location from INPUT_BUFFER}; LET Medication BE OBJECT [Drug_Name, Form, Dosage, Route, Schedule]; LET VAQTA BE Read As Medication {select med, form, dose, route, schedule from EHR where med = 'VAQTA'} ; LET HAVRIX BE Read As Medication {select med, form, dose, route, schedule from EHR where med = 'HAVRIX'} ; LET TWINRIX BE Read As Medication {select med, form, dose, route, schedule from EHR where med = 'TWINRIX'} ; Let GenericMessage BE OBJECT [MessageID, MessageCode, Message_Text]; Let Vaccine_Message BE New GenericMessage; [thus disclosing patient information and medication information] it does not fully disclose the following limitations Legere discloses:
The electronic medical system according to claim 1, wherein the medical- related information includes … medical staff information, test information, medical record information, symptom information, and diagnostic information. (Paras 60-63 discloses some visit types may include a data item indicating a diagnostic test appropriate for the visit type. For example, in some embodiments, a “flu” visit type may include a flu test strip, a “strep throat” visit type may include a strep test, among other visit types and associated tests [test information]. The test analysis service 260 may receive an image for the diagnostic test and automatically identify test results based on the received image. In some embodiments, the recommendation service 240 may recognize, e.g., via tags or metadata, types of HPI information, such as, e.g., chief complaint, symptoms, symptom details (e.g., duration, severity, etc.), medical history, medications, among other HPI information and medical history information [medical record information]. Para 83 discloses In some embodiments, the intake record 329 may be stored with the user profile 328 in the account associated with the user. Accordingly, a user’s account may include profile information, as well as a history of per-visit intake records 329 for each visit to the cloud platform [patient information]. Para 113 discloses the test results 665 may be appended to the intake record, or associated with the intake record using, e.g., a link based on the visit code as described above. Para 129 discloses the provider profile 830 [medical staff information] may include data representing the capabilities of the provider, such as, e.g., a practice area associated with the provider, the age range that the provider is qualified to treat (e.g., pediatrics, geriatrics, etc.), regions in which the provider is licensed to provide medical services, among other qualifications.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of the Arden Syntax Implementation Guide as taught by Jenders, the rules of the Arden Syntax of the system and method for presentation of computerized patient records across a network as taught by Moshfeghi, the medical information appliance as taught by Barker, the method of evaluating autoimmune disease risk and treatment selection as taught by Steinberg-Koch and the techniques for creating and utilizing multidimensional embedding spaces as taught by Walters with the automated dynamic generation of interface sequences for data record creation and methods of use thereof as taught by Legere in order to create a thorough records based on various types of data of the patient and to identify provider capabilities encoded in the provider profile.
While Legere discloses the above limitations, the combination of Jenders, Moshfeghi, Barkers, Steinberg-Koch, and Walters does not fully disclose the following limitations that Chaudhry discloses:
The electronic medical system according to claim 1, wherein the medical- related information includes patient information, diagnosis information, order information and treatment information (Para 78 discloses each search object can be appropriately labeled to indicate to the user which search will be initiated by each object. For example, and not limitation, the search objects can be labeled as "Dem," "ROS," "PMH," "PSH," "SH," "Med," "Alrg," "PE," "Img," "Diag," "Plan," "Labs," and "Rx," corresponding respectively to data in the categories of demographics, review of systems, past medical history, past surgical history, social history, current medications, allergies, physical examination, imaging studies results, diagnoses, treatment plan, lab orders, and prescriptions.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of the Arden Syntax Implementation Guide as taught by Jenders, the rules of the Arden Syntax of the system and method for presentation of computerized patient records across a network as taught by Moshfeghi, the medical information appliance as taught by Barker, the method of evaluating autoimmune disease risk and treatment selection as taught by Steinberg-Koch and the techniques for creating, utilizing multidimensional embedding spaces as taught by Walters and the automated dynamic generation of interface sequences for data record creation and methods of use thereof as taught by Legere with the medical record entry systems and methods as taught by Chaudhry in order to search for data related to treatment plan, lab orders, and prescriptions under objects.
Additional Prior art of Record
The following prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US PG Pub 2013/0332873 A1 as taught by Shapiro, Samuel
Learning vector representation of medical objects via EMR-driven nonnegative restricted boltzmann machines as taught by Tran
Response to Arguments
Applicant’s arguments filed 12/01/2025 with respect to 35 U.S.C. § 101 have been fully considered, but are not persuasive.
The Applicant argues that the claim limitations transform the claimed invention into a particular machine and is not directed to an abstract idea. The Examiner respectfully disagrees. See MPEP 2106.05(b) Particular Machine which states, “It is noted that while the application of a judicial exception by or with a particular machine is an important clue, it is not a stand-alone test for eligibility. Id… if a claim fails the Alice/Mayo test (i.e., is directed to an exception at Step 2A and does not amount to significantly more than the exception in Step 2B), then the claim is ineligible even if it passes the M-or-T test. DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1256, 113 USPQ2d 1097, 1104 (Fed. Cir. 2014) ("[I]n Mayo, the Supreme Court emphasized that satisfying the machine-or-transformation test, by itself, is not sufficient to render a claim patent-eligible, as not all transformations or machine implementations infuse an otherwise ineligible claim with an 'inventive concept.'").” Further, MPEP 2106.05(b)(I) states, “It is important to note that a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine. Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 716-17, 112 USPQ2d 1750, 1755-56 (Fed. Cir. 2014). See also TLI Communications LLC v. AV Automotive LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (mere recitation of concrete or tangible components is not an inventive concept).” As such, the Applicant’s argument that a medical record server, terminal, database and external medical modules that are physically interconnected is a particular machine is not persuasive. The claims disclose a general purpose computer that applies a judicial exception, mere recitation of concrete or tangible components is not an inventive concept. The argument that device communication cannot be performed by a human mind is not persuasive. Particularly, the Examiner submits that the abstract idea was not characterized as being directed to a mental process. And further, device communication (for example, by a network) would not be considered a part of the abstract idea, it would be considered an additional element and as such this argument is not persuasive. A server that is physically connected via the network to the medical staff terminal, a database of the server, and the external modules as amended to the independent claims is recited at a high-level of generality such that it amounts to no more than mere instructions to implement an abstract idea by adding the words ‘apply it’ (or an equivalent) with the judicial exception.
The Applicant further points to Example 42 while arguing that the limitations transform the claimed invention into a particular machine, not a conceptual system. The Examiner disagrees that this is shown in Example 42. In this example, claim 1 was found eligible because the claim as a whole integrates the method of organizing human activity into a practical application. Specifically, the additional elements recite a specific improvement over prior art systems by allowing remote users to share information in real time in a standardized format regardless of the format in which the information was input by the user. The claim was not purely eligible just because it claimed remote access over a network.
Further, the Applicant argues that the “statement script” is not a rule set, it is an executable object-oriented program and that Under Enfish and USPTO guidance, claims reciting specific executable code structures that improve system operation are not abstract. The Examiner agrees that Enfish and USPTO guidance indicate that specific executable code structure that improves system operation is not abstract. However, the claims of the instant application aren’t improving the system operation and as such this is not persuasive. In regards to the newly added limitation that claims the system “reduce[s] redundant database access and thereby improv[es] processing efficiency of the electronic medical record server by reducing data retrieval latency and redundant computation.” As presented above, there is no support for this limitation nor any explanation how the features of the claim nor the features described in the specification provide the claimed “improvements.” See MPEP 2106.05(f), “The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words “apply it”. See Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1356, 119 USPQ2d 1739, 1743-44 (Fed. Cir. 2016); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1327, 120 USPQ2d 1353, 1366 (Fed. Cir. 2016); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1417 (Fed. Cir. 2015).” As such, this argument is not persuasive.
The Applicant then argues that script is a machine-processable instruction and not an abstract rule. There is nothing in the 'statement script functions as a query' that removes it from being part of certain methods of organizing human activity. The query may be a "machine-processable instruction" but it may also be a human processable instruction. There is nothing associated with the statement script being a query that makes it inherently performable only on a computer.
The Applicant argues that the server performs database-structural transformations and that courts and USPTO examples consistently treat data structure updates and databasetransformations as technical processes. The Examiner agrees, but notes that these decisions/examples are eligible because the updates/transformation provide an improvement supported by the disclosure; these decisions/examples are not eligible merely because they claim an updated data structure or database transformation. Here there is no improvement.
Further, the Applicant states that embedding vectors are widely recognized in computer science as technical data structures, and compares it to the rule based sequences in McRO. Embedding vectors are data manipulations and are part of the abstraction. The Examiner also notes that the Applicant appears to admit that embedding vectors are well-understood, routine, and conventional in the art. The claimed invention is not comparable to McRO because the is no indication in the record that computers could not previously be programmed to perform the claimed features. Therefore, this argument is not persuasive.
The Applicant then argues that the system performs actual machine control of external medical modules. The Examiner respectfully disagrees. Transmitting or receiving data or control signals was found above to be insignificant extra solution activity and was found to be well-understood, routine, and conventional activity. The courts have recognized computer function of receiving or transmitting data over a network, e.g., using the internet to gather data as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
Further, transmitting or receiving a control signal does not result in controlling the external modules based on the server computations. Transmitting data to a module is not control of the module. The claim does not even require that the module(s) receive the data. There is also no control recited; merely transmission. Further, the claim language does not connect the analysis to the generation of the control signal or what the control signal is. As such, the data processing itself is not resulting in the machine control, the Applicant simply discloses the ability to potentially transmit the control signal.
Further, the claim language does not require the control signal to be transmitted or received as it states, “transmits or receives a control signal or patient physiological data to or from the external modules.” Therefore, it could be that patient physiological data that is transmitted or received.
The Applicant also argues that the architecture of the present invention is non-conventional, designed specifically to optimize electronic medical record update processes by: selectively recalculating embedding vectors, reducing redundant database access, minimizing latency and synchronizing external devices. As presented above, there is no support for this “improvement” in the specification nor any explanation how the features of the claim nor the features described in the specification provide the claimed “improvements.” See MPEP 2106.05(f), “The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words “apply it”. See Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1356, 119 USPQ2d 1739, 1743-44 (Fed. Cir. 2016); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1327, 120 USPQ2d 1353, 1366 (Fed. Cir. 2016); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1417 (Fed. Cir. 2015).” As such, this argument is not persuasive.
The Applicant argues that enabling vector-similarity operations and probabilistic inference across medical objects is not possible on conventional record-based electronic medical record databases. The Examiner notes that the specification page 5, lines 7-14 disclose, “Specifically, the electronic medical record server 100 includes a data processing unit 110, an input unit 120, an output unit 130, an external module connection unit 140, and a database 150.” The components of the electronic medical record server are not improved in any way and are not performing differently as expected. As such, this argument is not persuasive.
Patient tracking hardware does not transform the electronic medical record from a passive data store into an integrated control system. There is no limitation that discloses control of any device, hardware, or system. Retrieving or transmitting data does not disclose controlling of a device as has been addressed multiple times above. As such, this argument is not persuasive.
Applicant argues that execution of a statement script that updates object attributes directly within a database provides structural modification to the data. Updating data (objects) is not enough to provide a practical application or significantly more to an abstract idea. Therefore, this argument is not persuasive.
Applicant’s arguments filed 12/01/2025 with respect to 35 U.S.C. § 103 have been fully considered and are persuasive regarding the newly added limitations. Therefore, the previous 35 U.S.C. § 103 rejection has been withdrawn. However, upon further consideration, a new grounds of rejection under 35 U.S.C. § 103 necessitated by Applicant’s amendments as disclosed above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SARA J MORICE DE VARGAS whose telephone number is (703)756-4608. The examiner can normally be reached M-F 8:30-5:30 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Peter H. Choi can be reached on (469)295-9171. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SARA JESSICA MORICE DE VARGAS/Examiner, Art Unit 3681
/PETER H CHOI/Supervisory Patent Examiner, Art Unit 3681