DETAILED ACTION
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 .
Status of Claims
In the reply filed 11 September 2026 the following changes have been made: amendments to claims 1, 4 6, 9, 11-14, 17, and 19-23.
Claims 1, 3-8, 9, 11-16, 17, and 19-23 are currently pending and have been examined.
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, 3-8, 9, 11-16, 17, and 19-23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1
The claim(s) recite(s) subject matter within a statutory category as a process (claims 1, 3-8, 17, 19-21, and 23) and machine (claims 9, 11-16, and 22).
INDEPENDENT CLAIMS
Step 2A Prong 1
Claim 1 recites steps of
monitoring, by an event-streaming application implemented by one or more processors operating in real time within a distributed computing system, a stream of as the messages are communicated on the communication network from plural different sources of medical records to identify a new or updated record of the medical records, rather than collecting the messages into a batch before examining the messages;
identifying, by the event-streaming application, one or more suspect records from a system of record (SOR) database, the one or more suspect records identified as being potential matches to the new or updated record that is identified;
determining, using a neural network and a matching rule engine implemented as a software application by the one or more processors, that the one or more suspect records match the new or updated record by applying matching rules, the neural network outputting a probability or indication of a match between the new or updated record and each of the one or more suspect records, wherein the matching rule engine is used for independent authoring, testing, building, and deploying of new or modified matching rules for matching rule consumption at runtime while the event-streaming application continues to identify suspect records and the matching rule engine continues to determine whether records match using existing matching rules that are not being created or modified, without taking down or deactivating ongoing examination of records using the existing matching rules;
obtaining a person entity profile related to the new or updated record from a person entity database; and
merging the new or updated record with the one or more suspect records or splitting the new or updated record from the one or more suspect records based on the person entity profile that is obtained.
Claim 9 recites steps of
one or more data sync processors of a distributed computing system
configured to monitor a stream of messages from plural different sources of medical records as the messages are communicated to identify a new or updated record of the medical records, rather than collecting the messages into a batch before examining the messages;
a person matching engine separate from the data sync processors, the person matching engine comprising one or more processors configured to execute:
an event-streaming application configured to identify and obtain one or more
suspect records from a system of record (SOR) database, the one or more suspect records, being potential matches to the new or updated record:
a matching rule engine implemented as another software application by the
one or more processors and configured to determine that the one or more suspect records match the new or updated record by applying matching rules, the matching rule engine being used for independent authoring, testing, building, and deploying of new or modified matching rules for matching rule consumption at runtime while the event-streaming application continues to identify suspect records and the matching rule engine continues to determine whether records match using existing matching rules that are not being created or modified, without taking down or deactivating ongoing examination of records using the existing matching rules, the person matching engine also configured to obtain a person entity profile related to the new or updated record from a person entity database and to merge the new or updated
record with the one or more suspect records or split the new or updated record from the one or more suspect records based on the person entity profile that is obtained.
Claim 17 recites steps of
monitoring, by an event-streaming application implemented by one or more
processors and deployed across a plurality of worker nodes in a distributed computing system, a stream of messages from plural different sources of medical records as the messages are communicated to identify a new or updated record of the medical records, rather than collecting
the messages into a batch before examining the messages;
identifying, by the event-streaming application, one or more suspect records from a system of record (SOR) database, the one or more suspect records identified as being potential matches to the new or updated record that is identified;
determining, using a neural network and a matching rule engine implemented as a software application by the one or more processors, that the one or more suspect records match the new or updated record by applying matching rules, the neural network outputting a probability or indication of a match between the new or updated record and each of the one or more suspect records, wherein the matching rule engine is used for independent authoring, testing, building, and deploying of new or modified matching rules for matching rule consumption at runtime while the event-streaming application continues to identify suspect records and the matching rule engine continues to determine whether records match using existing matching rules that are not being created or modified, without taking down or deactivating ongoing examination of records using the existing matching rules;
obtaining a person entity profile related to the new or updated record from a person entity database, the person entity profile including source identifiers uniquely identifying which of the sources generated the medical records associated with each of several different persons; and
performing at least one of (a) merging the new or updated record with the one or more suspect records or (b) splitting the new or updated record from the one or more suspect records,
wherein, when the merging is performed, merging the new or updated record with the one or more suspect records occurs responsive to the source identifiers in the new or updated record and the one or more suspect records being associated with two or more of the different persons in the person entity database, and
wherein, when the splitting is performed, splitting the new or updated record from the one or more suspect records occurs responsive to the source identifiers in the new or updated record and the one or more suspect records being associated with a single person of the different persons in the person entity database along with one or more other source identifiers.
These steps for matching patient records, as drafted, under the broadest reasonable interpretation, includes methods of organizing human activity. That is, nothing in the claim precludes the italicized portions from managing personal behavior or relationships or interactions between people by organizing the activity around monitoring, identifying, determining, and merging and/or splitting a set of patient records. This could be analogized to manual file keeping operations, a task historically performed by humans (e.g., medical clerks). If a claim limitation, under its broadest reasonable interpretation, covers performance as organizing human activity but for the recitation of generic computer components, then it falls within the “Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A Prong 2
This judicial exception is not integrated into a practical application. In particular, the additional elements non-italicized portions identified above for claims 1, 9, and 17, do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more than limitations which:
amount to mere instructions to apply an exception (such as
recitation of [Claim 1] by an event-streaming application implemented by one or more processors operating in real time within a distributed computing system; on the communication network; by the event-streaming application; using a neural network and a matching rule engine implemented as a software application by the one or more processors; and, the matching rule engine is used. [Claim 9] one or more data sync processors of a distributed computing system; a person matching engine separate from the data sync processors, the person matching engine comprising one or more processors configured to execute: an event-streaming application; and, a matching rule engine implemented as another software application by the one or more processors. [Claim 17] by an event-streaming application implemented by one or more processors and deployed across a plurality of worker nodes in a distributed computing system; by the event-streaming application; and, using a neural network and a matching rule engine implemented as a software application by the one or more processors amounts to invoking computers as a tool to perform the abstract idea, see MPEP 2106.05(f))
add insignificant extra-solution activity to the abstract idea (such as recitation of [Claim 1] outputting a probability or indication of a match between the new or updated record and each of the one or more suspect records; and, obtaining a person entity profile related to the new or updated record from a person entity database. [Claim 9] obtain one or more suspect records from a system of record (SOR) database; and, obtain a person entity profile related to the new or updated record from a person entity database. [Claim 17] outputting a probability or indication of a match between the new or updated record and each of the one or more suspect records; and, obtaining a person entity profile related to the new or updated record from a person entity database amounts to mere data gathering and output since it does not add meaningful limitations to the obtaining and outputting performed, see MPEP 2106.05(g))
Each of the above additional elements therefore only amounts to mere instructions to implement functions within the abstract idea using generic computer components or other machines within their ordinary capacity, and add insignificant extra-solution activity to the abstract idea. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. These elements are therefore not sufficient to integrate the abstract idea into a practical application. Therefore, the above claims, as a whole, are directed to an abstract idea.
Step 2B
The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception and amount to no more than add insignificant extra-solution activity. Additionally, the additional limitations, other than the abstract idea per se, amount to no more than limitations which:
amount to mere instructions to apply an exception in particular fields such as recitation of [Claim 1] by an event-streaming application implemented by one or more processors operating in real time within a distributed computing system; on the communication network; by the event-streaming application; a matching rule engine implemented as a software application by the one or more processors; and, the matching rule engine is used. [Claim 9] one or more data sync processors of a distributed computing system; a person matching engine separate from the data sync processors, the person matching engine comprising one or more processors configured to execute: an event-streaming application; and, a matching rule engine implemented as another software application by the one or more processors. [Claim 17] by an event-streaming application implemented by one or more processors and deployed across a plurality of worker nodes in a distributed computing system; by the event-streaming application; and, a matching rule engine implemented as a software application by the one or more processors, e.g., a commonplace business method or mathematical algorithm being applied on a general-purpose computer, Alice Corp. v. CLS Bank, MPEP 2106.05(f).
[Claim 1] using a neural network; and, [Claim 17] using a neural network, e.g., requiring the use of software to tailor information and provide it to the user on a generic computer, Intellectual Ventures I LLC v. Capital One Bank., MPEP 2106.05(f).
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields such as recitation of [Claim 1] outputting a probability or indication of a match between the new or updated record and each of the one or more suspect records; and, obtaining a person entity profile related to the new or updated record from a person entity database. [Claim 9] obtain one or more suspect records from a system of record (SOR) database; and, obtain a person entity profile related to the new or updated record from a person entity database. [Claim 17] outputting a probability or indication of a match between the new or updated record and each of the one or more suspect records; and, obtaining a person entity profile related to the new or updated record from a person entity database, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i).
Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide generic computer implementation.
DEPENDENT CLAIMS
Step 2A Prong 1
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims (such as claims 3-8, 11-16, and 19-23 reciting particular aspects for matching patient records such as
[Claims 3] wherein the one or more suspect records are determined to match the new or updated record by the matching rule engine, which compares information contained within the one or more suspect records and the new or updated record using matching rules;
[Claim 4] authoring one or more new rules or one or more changes to the matching rules off-line using the matching rule engine while the matching rules without the one or more new rules or the one or more changes continue to be used to determine whether the one or more suspect records match the new or updated record, and deploying the one or more new rules or the one or more changes for matching rule consumption at runtime;
[Claim 5] testing the one or more new rules or the one or more changes to the matching rules off-line using the medical records without merging the new or updated record with the one or more suspect records and without splitting the new or updated record from the one or more suspect records;
[Claims 6 & 14] wherein the one or more suspect records include plural suspect records, and further comprising:
determining that two or more of the suspect records match each other using the matching rule engine in the distributed computing system; and
merging the two or more of the suspect records with each other;
[Claims 7 & 15] wherein the medical records include source identifiers uniquely identifying which of the sources generated the medical records and the person entity database stores the source identifiers associated with each of several different persons,
wherein merging the new or updated record with the one or more suspect records occurs responsive to the source identifiers in the new or updated record and the one or more suspect records being associated with two or more of the different persons in the person entity database;
[Claims 8 & 16] wherein the medical records include source identifiers uniquely identifying which of the sources generated the medical records and the person entity database stores the source identifiers associated with each of several different persons,
wherein splitting the new or updated record from the one or more suspect records occurs responsive to the source identifiers in the new or updated record and the one or more suspect records being associated with a single person of the different persons in the person entity database along with one or more other source identifiers;
[Claim 11] wherein the matching rule engine is configured to determine the one or more suspect records are determined to match the new or updated record by comparing information contained within the one or more suspect records and the new or updated record using matching rules applied in real time;
[Claim 12] wherein the matching rule engine is configured for independent authoring of one or more new rules or one or more changes to the matching rules off-line while the matching rules without the one or more new rules or the one or more changes continue to be used to determine whether the one or more suspect records match the new or updated record and for deploying the one or more new rules or the one or more changes for matching rule consumption at runtime;
[Claim 13] wherein the matching rule engine is configured to test the one or more new rules or the one or more changes to the matching rules off-line using the medical records without merging the new or updated record with the one or more suspect records and without splitting the new or updated record from the one or more suspect records in the person entity database;
[Claim 19] wherein the one or more suspect records are determined to match the new or updated record by the matching rule engine by comparing information contained within the one or more suspect records and the new or updated record using matching rules applied in real time, and further comprising:
authoring one or more new rules or one or more changes to the matching rules using the matching rule engine off-line while the matching rules without the one or more new rules or the one or more changes continue to be used to determine whether the one or more suspect records match the new or updated record; and deploying the one or more new rules or the one or more changes for matching rule consumption at runtime;
[Claim 20] testing the one or more new rules or the one or more changes to the matching rules off-line using the medical records without merging the new or updated record with the one or more suspect records and without splitting the new or updated record from the one or more suspect records in the person entity database;
[Claim 21] training the neural network using historical patient data to derive one or more matching rules defining a machine learning model for analyzing input patient records; and, responsive to feedback from manual correction of an overmatch or undermatch output by the neural network, modifying one or more weights, parameters, rules, criteria, or thresholds used by neurons of the neural network and repeating analysis of patient records using the modified one or more weights, parameters, rules, criteria, or thresholds to reduce overmatching or undermatching;
[Claim 22] neural network configured to output an indication or probability that the one or more suspect records match the new or updated record based on a machine learning model wherein the neural network is configured to be trained using historical patient data to derive one or more sets of matching rules defining a machine-learning model for analyzing input patient records, the neural network configured to, responsive to feedback from manual correction of an overmatch or undermatch output by the neural network, modify one or more weights, parameters, rules, criteria, or thresholds used by neurons of the neural network and to repeat analysis of patient records using the modified one or more weights, parameters, rules, criteria, or thresholds to reduce overmatching or undermatching;
[Claim 23] training the neural network using historical patient data to derive one or more matching rules in a machine-learning model for analyzing input patient records; and, responsive to feedback from manual correction of an overmatch or undermatch output by the neural network, modifying one or more weights, parameters, rules, criteria, or thresholds used by neurons of the neural network and repeating analysis of patient records using the modified one or more weights, parameters, rules, criteria, or thresholds to reduce overmatching or undermatching;
these italicized portions are methods of organizing human activity since they merely describe types of data and determinations that can be performed by humans.
Step 2A Prong 2
Dependent claims 3-4, 6, 11-14, 19, and 21-23 recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (the additional limitations in claim 3 (by the matching rule engine); claim 4 (using the matching rule engine configured for independent authoring and hot deployment); claim 6 & 14 (using the matching rule engine in the distributed computing system); claims 11 (matching rule engine); claim 12 (matching rule engine); claim 13 (the matching rule engine); claim 19 (using the matching rule engine); claim 21 (applying, by the matching rule engine, a machine learning model that is used by the neural network; and, periodically retraining the machine learning model); claim 22 (the person matching engine is configured to apply a machine model that is used by the person matching engine; and, the person matching engine configured to periodically retrain the machine learning model); and, claim 23 (applying, by the neural network, a machine learning model; and, periodically retraining the machine learning model) amounts to invoking computers as a tool to perform the abstract idea, see MPEP 2106.05(f)); and, add insignificant extra-solution activity to the abstract idea such as recitation of claim 22 (output an indication or probability that the one or more suspect records match the new or updated record) amounts to mere data output since it does not add meaningful limitation to the outputting performed, see MPEP 2106.05(g))). Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Step 2B
Dependent claims 3-4, 6, 11-14, and 19 recite additional subject matter which, as discussed above with respect to integration of the abstract idea into a practical application, amount to invoking computers as a tool to perform the abstract idea, e.g., a commonplace business method or mathematical algorithm being applied on a general-purpose computer, Alice Corp. v. CLS Bank, MPEP 2106.05(f). Dependent claims 21-23 recite additional subject matter which, as discussed above with respect to integration of the abstract idea into a practical application, amount to invoking computers as a tool to perform the abstract idea, e.g., requiring the use of software to tailor information and provide it to the user on a generic computer, Intellectual Ventures I LLC v. Capital One Bank., MPEP 2106.05(f). Also, see [0112] which provides examples of off-the-shelf processors and memory. Dependent claim 22 recites additional subject matter which amounts to elements that have been recognized as well-understood, routine, and conventional activity, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i). There is no indication that these additional elements improve the functioning of a computer or improves any other technology. Their collective functions merely provide generic computer implementation.
Therefore, in consideration of all the facts, the present invention is still not a patent-eligible invention under USC 101. Additionally, it is evident that the present claims monopolize using algorithms to match and merge medical records, restricting further innovation in this area without offering a specific, technical improvement to how the computer actually operates; “monopolization of those tools through the grant of a patent might tend to impede innovation more than it would tend to promote it.” Alice Corp., 573 U.S. at 216, 110 USPQ2d at 1980 (quoting Myriad, 569 U.S. at 589, 106 USPQ2d at 1978 and Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 (2012)).
Response to Arguments
Applicant’s arguments filed on 13 April 2026 & 19 May 2026 have been considered but are not fully persuasive.
Regarding the USC 112 interpretation, applicant has amended the claims to not recite a 112(f) interpretation. Therefore, the claims are no longer interpreted under USC 112(f).
Regarding the USC 112(a) rejection, applicant has amended the claims to satisfy the written description requirement. Therefore, the USC 112(a) rejection has been withdrawn.
Regarding the USC 101 rejection, applicant argues that amended claims 1, 9, and 17 do not merely recite the result of "matching records" and are instead directed to computer operation recitations, especially with the worker nodes of claim 17, that cannot be practically performed mentally or with pen and paper.
Examiner disagrees with the applicant’s arguments. While applicant is trying to clarify the claim language with amendments, examiner asserts that the claims are still directed to the judicial exception(s) as confirmed by multiple subject matter experts at the USPTO. Applicant’s invention, at its core, describes steps that can be (and historically have been) performed by a humans. That is, the core of the claim is for managing, matching, and deduplicating medical records using neural networks and rule engines. Applying rules in an event-streaming context that continually updates a database does not make this a patent eligible invention. Human medical record clerks have looked at conflicting files, applied rules (e.g., date of birth matches and last name is hyphenated), and updated a master index for over a century. Applicant asserts that the tasks in claim 1 are not an abstract idea, but examiner disputes this and asserts that the analogy (under BRI) correctly identifies the logic and organizational steps that are identical to manual methods. For example, a team of clerks divide the labor: Clerk A continuously monitors an incoming fax machine, Clerk B cross-references a master paper filing cabinet, and Clerk C updates a card catalog with a red marker indicating a record is split. This division of labor mirrors every step of claim 1 (as confirmed by multiple subject matter experts at USPTO). Managing, organizing, updating, and verifying medical records is a long-standing administrative and business practice (commercial/legal relationships or managing data workflows). Sorting through files to see if a patient already has an existing folder ("suspect records") before creating a duplicate or merging them is a fundamental clerical task. Applicant’s claims recites various software components, but these limitations are viewed as functional results rather than an implementation of a specific, tangible technical mechanism. Simply taking a known abstract task (i.e., record matching) and splitting its workflow execution across generic computer components does not change the abstract nature of the claim. The inclusion of "worker nodes in a distributed computing system" in claim 17 does not save a claim from being classified as an abstract idea at this stage for two primary reasons: 1) they are treated as generic hardware 2) they implement the abstract idea rather than being the invention. Examiner points to the USPTO October 2019 Guidance (also incorporated in MPEP 2106) states that claims can recite an abstract idea even if they are claimed as being performed on a computer. The USPTO October 2019 Guidance is clear in that the courts have found claims requiring a generic computer or nominally reciting a generic computer may still recite an abstract idea even though the limitations may not be entirely performed by humans. The computer components recited in the present application are still recited at a high level of generality. The computers in the claims are not used in a specific, inventive way. Again, the claims are very outcome-focused and do not detail how each of the outcomes are exactly reached. Merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94 (Fed. Cir. 2015) ("Just as Diehr could not save the claims in Alice, which were directed to ‘implement[ing] the abstract idea of intermediated settlement on a generic computer’, it cannot save OIP's claims directed to implementing the abstract idea of price optimization on a generic computer.") (citations omitted). Even if the claims nominally recites computer components that are rooted in technology, there is no recitation of how the computer components are specifically programmed to distinguish from generic computer processes. Thus, the present claim(s) are still not eligible under Step 2A Prong 1
For Step 2A Prong 2, applicant asserts that the amended independent claims integrate any such concept into a practical application by further requiring monitoring the messages as the messages are communicated rather than collecting the messages into a batch before examination. Applicant ties various paragraphs of the specification as describing the specific improvement. Applicant even asserts that the present claims are similar to Ex parte Desjardins. Recentive is also cited with the assertion that in the present application patent eligibility does not rest on the proposition that merely adding a neural network to patient-record matching is inventive. Rather, the claims instead recite a particular software architecture and concurrency/availability mechanism governing how live event-stream processing continues during rule evolution.
Examiner disagrees with the applicant’s arguments. There is no quantitative indication in the claims that even suggest performing large volume. The core "innovation" described is the ability to author, test, and deploy new rules at runtime without taking down the system. While this is highly convenient software engineering, patent courts (like the Federal Circuit) view this as an optimization of software logic or administrative workflow, not a fundamental improvement to the underlying computer hardware, processing speed, or network security. The claim does not disclose (nor can the applicant argue) a new processor design or even a new network communication protocol. All this invention is doing is taking standard, off-the-shelf engineering concepts and directs them to process application-level data. And so, rearranging the layout of generic computer components that the applicant did not invent does not constitute a technological improvement to the computer itself. It is clearly a mere automation of an administrative human workflow. It is also clearly evident from the applicant’s explanation of the invention that they believe attempting to take highly complex and off-the-shelf distributed tooling (like Kafka or Spark CEP) deploying it to solve a messy healthcare data issue, they’ve somehow engineered a “novel architecture.” All the applicant is doing is applying known technology for their intended benefit(s) to a new data environment and calling it an improvement (see Customedia Techs., LLC v. Dish Network Corp., Case No.18-2239 (Fed. Cir. Mar. 6, 2020); the underlying problem outlined in the specification is not a flaw in computer networks, memory allocation, or server architecture, but rather demographic volatility and typographical errors; problems that existed long before computers were even invented. Examiner asserts the present specification provides a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art. Examiner asserts it is also not clear how the invention provides an improvement. Specifically, examiner reasserts the following factual determinations which the applicant has been unable to dispute and counters the applicant’s arguments of practical application:
First, one of ordinary skill in the art would recognize that implementing a distributed, event-driven neural network for tasks that could be handled by high-performance deterministic indexing may introduce unnecessary architectural complexity and higher maintenance costs without a proportional increase in accuracy. The applicant’s specification does not explain/lacks detail on how architectural complexity and higher maintenance costs are managed that is necessary for an improvement to be apparent to a person of ordinary skill in the art. Thus, it is not evident from the specification how the amended claims improve the operation of computers.
Second, one of ordinary skill in the art would recognize that hot deploying matching rules in a distributed environment commonly fails due to consistency issues, network partitions, or improper state management. Specific failure modes include, but are not limited to, inconsistent rule application across nodes, partial updates where only a subset of nodes receive the new rules, rule conflicts during live updates, and increased latency or downtime during propagation. The applicant’s specification does not explain/lacks detail on how failure modes are managed that is necessary for an improvement to be apparent to a person of ordinary skill in the art. Thus, it is not evident from the specification how the amended claims improve the operation of computers.
Third, one of ordinary skill in the art would recognize that while event-streaming (like Kafka) is fast, invoking a neural network for every suspect record comparison can become a computational bottleneck. If the system identifies 100 suspect records for one update, the inference time multiplied across the applicant’s asserted “billions” of messages may negate the real-time benefits of the streaming architecture. The applicant’s specification does not explain/lacks detail on how computational bottlenecks are managed that is necessary for an improvement to be apparent to a person of ordinary skill in the art. Thus, it is not evident from the specification how the amended claims improve the operation of computers.
Fourth, one of ordinary skill in the art would recognize that flagging records as “not-for-production” or “inactive” within the same database used for live resolution can lead to database bloat and slower query performance over time. The applicant’s specification does not explain/lacks detail on how database bloat and slower query performance are managed that is necessary for an improvement to be apparent to a person of ordinary skill in the art. Thus, it is not evident from the specification how the amended claims improve the operation of databases themselves.
The MPEP provides that improvements to the functioning of a computer or to any other technology or technical field can signal eligibility, see MPEP 2106.05(a), and provides examples of improvements to computer functionality, MPEP 2106.05(a)(I), and improvements to any other technology of technical field, MPEP 2106.05(a)(I). “In computer-related technologies, the examiner should determine whether the claim purports to improve computer capabilities or, instead, invokes computers merely as a tool”. Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1336, 118 USPQ2d 1684, 1689 (Fed. Cir. 2016). In Enfish, the court evaluated the patent eligibility of claims related to a self-referential database. Id. The court concluded the claims were not directed to an abstract idea, but rather to an improvement to computer functionality. Id. It was the specification' s discussion of the prior art and how the invention improved the way the computer stores and retrieves data in memory in combination with the specific data structure recited in the claims that demonstrated eligibility. 822 F.3d at 1339, 118 USPQ2d at 1691. The claim was not simply the addition of general-purpose computers added post-hoc to an abstract idea, but a specific implementation of a solution to a problem in the software arts. 822 F.3d at 1339, 118 USPQ2d at 1691. Unlike Enfish, the instant claimed invention appears to improve upon a judicial exception rather than a problem in the software arts. Rather than improving a computer's algorithm (i.e., solving a technically based problem), the claimed invention purports to solve the non-technological problems of demographic volatility, typographical errors, overmatching and undermatching of patients ([0001] to [0004] of specification) by using computers to automate patient record matching. In other words, one of the main/glaring issues with the present invention is that the problem solved by the applicant is not a technological problem.
The examiner asserts the following facts the applicant has been unable to dispute:
1) the invention does NOT involve a novel algorithm or data structure that significantly improves the computer's functionality,
2) the invention does NOT involve a new hardware component or configuration that works with the computer to achieve a specific technical benefit, and
3) the computer is NOT used in a completely new way demonstrating a significant technical advancement.
It is evident from the specification and claims that the applicant is not improving computer technology, and instead providing an improvement to the abstract idea by automation of human tasks. Applicant’s specification [0131] literally admits examination of medical records can be performed mentally or with pen and paper. An improvement to the abstract idea is not an improvement to computer technology. Thus, examiner does not see how the present claims improve the functioning of a computer or provide improvements to any other technology or technical field. The claimed invention appears similar to the example of improvements that are insufficient to show an improvement in computer-functionality such as arranging transactional information on a graphical user interface in a manner that assists traders in processing information more quickly, Trading Technologies v. IBG LLC, 921 F.3d 1084, 1093-94, 2019 USPQ2d 138290 (Fed. Cir. 2019). See MPEP 2106.05(a)(I)(viii). The broad claims are lacking concrete limitations to integrate the abstract idea into a practical application. Examiner points out that the claimed limitations have no indication in the specification that the operations recited invoke any inventive programming, require any specialized computer hardware or other inventive computer components, i.e., a particular machine, or that the claimed invention is implemented using other than generic computer components to perform generic computer functions. See DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1256 (fed Cir. 2014) (“[A]fter Alice, there can remain no doubt: recitation of generic computer limitations does not make an otherwise ineligible claim patent-eligible.”). Most importantly, in DDR Holdings & unlike the present claims, the claims at issue specified how interactions with the Internet were manipulated to yield a desired result—a result that overrode the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink. 773 F.3d at 1258; 113 USPQ2d at 1106. The examiner also points out that there is no indication in the specification that the claimed invention affects a transformation or reduction of a particular article to a different state or thing. Examiner points to the recitation of neural network in the claim(s) is generic. "[T]he mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention." Alice Corp. v. CLS Banklnt'l, 573 U.S. 208 223 (2014). Applicant does not and cannot contend they invented the concept of neural networks, nor does the specification disclose any new neural network technique. In fact, the applicant’s specification [0115] recognizes known neural networks in the art. The alleged improvement of using a neural network lies in the abstract idea itself, not to any technological improvement nor to any improvement to the functioning of a computer. See BSG Tech LLC v. Buyseasons, Inc., 899 F.3d 1281, 1287-88 (Fed. Cir. 2018). The fact pattern of the applicant’s claims is congruent to the Recentive Analytics, Inc. v. Fox Corp., 2025 U.S.P.Q.2d 628 (Fed. Cir. 2025) decision by the Federal Circuit. Just like in Recentive, the present claims do not delineate steps through which the neural network technology achieves an improvement. See, e.g., IBM v. Zillow Grp., Inc., 50 F.4th 1371, 1381 (Fed. Cir. 2022) (holding abstract a claim that "d[id] not sufficiently describe how to achieve [its stated] results in a non-abstract way," because "[s]uch functional claim language, without more, is insufficient for patentability under our law." (quoting Two-Way Media Ltd v. Comcast Cable Commc'ns, LLC, 874 F.3d 1329, 1337 (Fed. Cir. 2017))); see also Intell. Ventures I LLC v. Capital One Fin. Corp., 850 F.3d 1332, 1342 (Fed. Cir. 2017) (similar); Elec. Power Grp., LLC v. Alstom S.A., 830 F.3d 1350, 1356 (Fed. Cir. 2016) (similar). Claiming a mere concept or functional result without disclosing the implementation details does not overcome USC 101. Applying an established technique to a new field or data set is insufficient for patent eligibility. The present claims are absolutely not similar to Ex parte Desjardins which recited a technological improvement to how the machine-learning system operates; not true for the present application. Examiner further points out that improving efficiency by reduction of latency (pg. 13 to 14 of the applicant’s arguments of record on 11/11/2025) is not sufficient to show an improvement in computer functionality as set forth by the courts in Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015); claiming the improved speed or efficiency inherent with applying the abstract idea on a computer does not integrate a judicial exception into a practical application or provide an inventive concept. This further supports the examiner’s assertion that the claims do not integrate a judicial exception into a practical application. To show an involvement of a computer assists in improving technology, the claims must recite details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology (MPEP 2106.05(a)(II)). In Finjan, Inc. v. Blue Coat Systems the courts found that the claims were “directed to a non-abstract improvement in computer functionality…” (MPEP 2106.04(d)). The present invention clearly does not meet the condition set forth by the courts and thus is not integrated into a practical application.
On pages 16 to 17 the applicant argues that for Step 2B the ordered combination is not generic computers and recites significantly more. That there is no prior-art rejection is being made and so the specific ordered combination should not be dismissed as merely generic computer implementation. Applicant asserts that the office action does not identify evidence and that the dependent claims are also patent eligible since they recite concrete operations. Applicant requests withdrawal of the USC 101 rejection.
Examiner disagrees with the applicant’s arguments. Examiner points out that the “apply it” analysis and “well-understood, routine, and conventional” analysis was performed under Step 2B, with court case citations, which didn’t result in the claim being eligible under USC 101. Examiner reminds the applicant that the MPEP makes it clear that the search for a 101 inventive concept is distinct from demonstrating 102 novelty. In addition, examine reminds the applicant that the search for an inventive concept is different from an obviousness analysis under 35 U.S.C. 103. See, e.g., BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341, 1350, 119 USPQ2d 1236, 1242 (Fed. Cir. 2016). Because they are separate and distinct requirements from eligibility, patentability of the claimed invention under 35 U.S.C. 102 and 103 with respect to the prior art is neither required for, nor a guarantee of, patent eligibility under 35 U.S.C. 101. In comparison to Bascom, examiner points out that Bascom is not similar to the present application because Bascom claimed a technical improvement in the art i.e., a technology-based solution to filter content on the internet while the present application is not presenting an improvement (as indicated above). Applicant’s specification never really sets out to solve problems with computer technology and instead acknowledges benefits of using off-the-shelf computer technology. The use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general-purpose computer or computer components after the fact to an abstract idea does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). The applicant has not demonstrated that their invention is inventive. Thus, the present invention is not patent-eligible under USC 101. Therefore, the USC 101 rejection is strongly maintained.
Prior Art Cited but Not Relied Upon
Zervas, M., & Karakasidis, A. (2024). Towards Split Learning-based Privacy-Preserving Record Linkage. arXiv preprint arXiv:2409.01088.
This reference is relevant because it discloses record matching through splitting.
US20210158907A1
This reference is relevant it is the applicant’s own reference with parallel disclosure on patient record matching.
US20230088474A1:
This reference is relevant it is the applicant’s own reference with parallel disclosure on patient record matching.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/WINSTON R FURTADO/Primary Examiner, Art Unit 3687
