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 .
The following is a non-final Office action on the merits in response to Application filed on 5/22/2024. Claims 1-13 are examined and pending.
Response to Amendment
The amendment filed on 5/22/2024 cancelled no claim. No claim was previously cancelled. New claims 12-13 are added. Claims 3-7, 10-11 have been amended. Therefore, claims 1-13 are examined and allowed.
Priority
Acknowledgment is made of applicant's claim for foreign priority based on application filed in France (FR), filed on 11/23/2021, and the instant application is a 371 of PCT/EP2022/082993, filed 11/23/2022.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 5/14/2026, follows the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
However, the information disclosure statement (IDS) submitted on 5/22/2024 does not follow the provisions of 37 CFR 1.97. The non-patent literature (NPL) shown in the IDS has Not been received.
Accordingly, these documents that has been lined through have not been received and thus not been considered as to the merits.
Applicant is advised that the date of any re-submission of any item of information contained in this information disclosure statement or the submission of any missing element(s) will be the date of submission for purposes of determining compliance with the requirements based on the time of filing the statement, including all certification requirements for statements under 37 CFR 1.97(e). See MPEP § 609.05(a).
Claim Objections
Claim 3, 9 are objected to because of the following informalities:
Claim 3 recites “wherein the received data 20…”, it is unclear what is received data 20 and what if refers to.
Claim 9 recites “wherein the function is an adversarial neural network. 20”, it is unclear what is “adversarial neural network. 20 “, and what if refers to.
Appropriate correction is required.
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 1-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Alice Corp. also establishes that the same analysis should be used for all categories of claims, regardless of a system/apparatus, a method, or a product claim.
The claimed invention (Claims 1-13) is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claim(s) recite(s) abstract ideas including “Certain Methods of Organizing Human Activity”, “an idea “of itself”, which have been identified/found by the courts as abstract ideas in new 101 memos of the subject matter eligibility in here (https://www.uspto.gov/patent/laws-and-regulations/examination-policy/subject-matter-eligibility) including 2019 Revised Patent Subject Matter Eligibility Guidance. This judicial exception is not integrated into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because It/they is/are recited at a high level of generality and/or are recited as performing generic computer functions routinely used in the computer applications:
Independent claim 1 (Step 2A, Prong I): is directed to multiple abstract ideas including “Certain Methods of Organizing Human Activity”, and “Mental process”.
Claim 1, Steps of,
receiving data relating to the care pathway of a patient,
determining, from the data relating to the care pathway of the patient, whether the patient belongs to one of a set of predefined groups, each group being associated with a set of predefined data, to obtain a determined group and a set of predefined determined data,
searching, for each predefined determined data, of the value of the predefined data of the patient, to obtain a set of values specific to the patient, and
applying a neural network to the patient-specific values to obtain a risk of the occurrence of sudden death for the patient, the neural network being specific to the determined group.
fall within “Certain Methods of Organizing Human Activity” grouping of abstract idea because these steps mainly describe the instant steps “collecting/receiving data, determining data, searching values, applying a neural network…”, which are human activities and/or interactions between users/people/devices and therefore, certain methods of organizing human activity which encompasses both certain activity of a single person, certain activity that involves multiple people, and certain activity between a person and a computer.
In addition, claim 1, steps mentioned above also falls within the abstract “Mental Processes” grouping of abstract ideas since these limitation covers performance of the limitations in the mind. For example, a human being can observe/collect/receive data, can evaluate/determine the data, can observe/search for the values, can observe/apply/use neural network technique.
Independent claim 1, Step 2A (Prong II): Accordingly, the claim recites an abstract idea(s) as pointed out above. This judicial exception(s) is/are not integrated into a practical application. In particular, the claim recites additional element (computer implemented in the preamble). Other than reciting “computer implemented “, nothing in the claim element precludes the step from practically being performed in the mind. There is no specificity regarding any technology, just broadly, execute the programming instructions to collect data, couple of databases to store data, determine data, searching data, apply neural network technique, run the data. Thus, the server/computer, databases, are not an essential element to actually create, change, or display functionality, and is simply used as a tool to automate the mental tasks. Applicant simply use a generic processor/server/computing device as a tool to implement the abstract ideas. The Examiner notes the instant claimed invention is in fact merely carried out by a generically recited computing platform; that is, essentially any computing system as seen in the applicant’s specification. The additional element limitations are simply a field of use that attempt to limit the abstract idea to a particular technological environment. The type of information being manipulated does not impose meaningful limitations or render the idea less abstract. Further the courts have found that simply limiting the use of the abstract idea to a particular environment does not add significant more.
Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. There is neither improvement to another technology or technical field nor an improvement to the functioning of the computer itself, and does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Independent claim 1 (step 2B): There are additional elements (i.e. computer implemented recited in the preamble) in claim 1. This additional element is recited at high level of generality and are generic computing components, and add nothing of substance to the underlying abstract idea; thus, they are not significantly more than the identified abstract idea.
These components are merely recited at a high level of generality and/or are recited as performing generic computer functions routinely used in the computer applications; thus, they are not significantly more than the identified abstract idea. Generic computer/device components recited as performing generic computer functions that are well-understood, routine and convention activities amount to no more than implementing the abstract idea with a computerized system. The use of generic computer components to receive/transmit/present/display information does not impose any meaningful limit on the computer implementation of the abstract idea. At best, the claim(s) are merely providing an environment to implement the abstract idea. (see analysis in claim 1).
According to MPEP 2106.05 (d), elements that the Courts have recognized as well-understood, routine, conventional activity in particular fields are e.g., "Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward
information); Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93” (evidence required by Berkeimer memo). Further, according to Berkheimer memo 04/19/2018, section III.A.1, “A specification demonstrates the well-understood, routine, conventional nature of additional elements when it describes the additional elements as well-understood or routine or conventional (or an equivalent term), as a commercially available product, or in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a)”.
Applicant’s Specification, [Fig. 1] indicate a general-purpose computer perform the instant steps and demonstrates the well-understood, routine, conventional nature of the information processing device (a processor/a computer) in any computing implementation. In other word, in light of the description in the specification as mentioned above with respect to paras [Fig. 1]), the Specification demonstrates that the additional elements must be sufficiently well-known. Thus, evidence has been provided to show these additional elements are well-understood, routine, conventional activity according to Berkheimer memo. Therefore, for the above mentioned reasons, viewed as a whole, even in combination, the above steps do not amount to significantly more/do not provide an inventive concept.
The procedural limitation “applying a neural network…” is specified at a high level of generality and is just recite as a name “neural network”. A person can use any “AI technique, for example, can put any information into an existing machine learning model and run the model”, and is simply organized information through human activity or merely mental tasks, and is part of, or a related, judicial exception and does not meaningfully limit the application of the identified judicial exception, and as such does not constitute significantly more.
Furthermore, the reciting of “applying a neural network …” merely using “neural network” as a tool to perform an existing machine learning model/process and/or merely adding the words "apply it" to the judicial exception. See MPEP 2106.05(f).
(1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished.
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process.
(3) The particularity or generality of the application of the judicial exception.
Thus, it is the solution of improving the abstract idea but not an improvement to another technology or technical field nor an improvement to the functioning of the computer itself. Applicant merely define a set of desirable results rather than defining a particular technology for achieving the set of desirable results. The Examiner notes the instant claimed invention is in fact merely carried out by a generically recited computing platform; that is, essentially any computing system as seen in the applicant’s specification. and as such does not constitute significantly more.
Dependent claims. 2-13, are merely add further details of the abstract steps/elements recited in claims 1 without including an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, dependent claims 2-13 are also non-statutory subject matter.
Viewed as a whole, the claims (1-13) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself.
Thus, the claims do NOT recite limitations that are “significantly more” than the abstract idea because the claims do not recite an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment.
Thus, the claimed invention, as a whole, does not provide 'significantly more' than the abstract idea, and is non-statutory subject matter.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 3-5, 10, 11, 12, 13 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Krishnamurti et al. (herein Krishnamurti, US 2020/0051697).
As per claim 1, 10, 11, Krishnamurti discloses a method, a computer program product [0020], a readable information medium [0020], for predicting the risk of the occurrence of a sudden death in a patient, the method being computer implemented and comprising the steps of:
receiving data relating to the care pathway of a patient ([0024, 0054, 0083]),
determining, from the data relating to the care pathway of the patient, whether the patient belongs to one of a set of predefined groups, each group being associated with a set of predefined data, to obtain a determined group and a set of predefined determined data ([0019, 0025, 0054, 0056, 0058, 0079, 0080, Table 1),
searching, for each predefined determined data, of the value of the predefined data of the patient, to obtain a set of values specific to the patient ([0021, 0041, 0045, 0055, 0057, 0059, 0060, 0079, 0083]), and
applying a neural network to the patient-specific values to obtain a risk of the occurrence of sudden death for the patient, the neural network being specific to the determined group ([0039, 0041, 0042]).
As per claim 3, Krishnamurti further discloses, wherein the received data 20 is data relating to the care pathway of the patient during the previous five years (Examine Note: “during the previous 5 years” is merely designer choice which does not impact the scope of the invention, therefore no patentable weight is given. For sake of prosecution, Krishnamurt does teaches collecting care data [0021, 0041, 0045, 0055, 0057, 0059, 0060, 0083, 0174]).
As per claim 4, Krishnamurti further discloses, wherein each predefined data is the presence of a disorder or the intake of a drug ([0056, 0057, 0059]).
As per claim 5, Krishnamurti further discloses, wherein the number of predefined data of a group is between 10 and 30 (Examine Note: “number of predefined data of a group is between 10 and 30” is merely designer choice which does not impact the scope of the invention, therefore no patentable weight is given. For sake of prosecution, Krishnamurt does teach a plurality of predefined data [0019, 0025, 0054, 0056, 0058, 0079, 0080, Table 1, 0082]),
As per claim 12, Krishnamurti further discloses,
wherein the number of predefined data of a group is between 15 and 25 ([0019, 0025, 0054, 0056, 0058, 0079, 0080, Table 1).
As per claim 13, Krishnamurti further discloses, wherein the number of 25 predefined data of a group is equal to 20 (Examine Note: “the number ….is equal to 20” is merely designer choice which does not impact the scope of the invention, therefore no patentable weight is given. For sake of prosecution, Krishnamurt does teach [0019, 0025, 0054, 0056, 0058, 0079, 0080, Table 1]).
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 2 is rejected under 35 U.S.C. 103 as being unpatentable over Krishnamurti et al. (herein Krishnamurti, US 2020/0051697), in view of
NPL1--Kim J, Park YR, Lee JH, Lee JH, Kim YH, Huh JW. Development of a Real-Time Risk Prediction Model for In-Hospital Cardiac Arrest in Critically Ill Patients Using Deep Learning: Retrospective Study. JMIR Med Inform. 2020 Mar 18;8(3):e16349. doi: 10.2196/16349. PMID: 32186517; PMCID: PMC7113801. (Year: 2020)
(herein NPL1)
As per claim 2, Krishnamurti further discloses, however, Krishnamurti does not explicitly disclose, wherein each neural network is a recurrent gated neural network.
NPL1 teaches (p.2, Second, we created a data pipeline to fit a gated recurrent unit (GRU) algorithm structure (see Data structure settings in Figure 2), p.4, Character-level gated recurrent unit (Char-GRU) is often used to predict the next token given a sequence of previous tokens).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Krishnamurti to include “recurrent gated neural network”, taught by NPL1. One would be motivated to do this in order to perform analysis work for clarifying and predicting a patient’s sudden death possibility.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Krishnamurti et al. (herein Krishnamurti, US 2020/0051697), in view of
NPL1--Kim J, Park YR, Lee JH, Lee JH, Kim YH, Huh JW. Development of a Real-Time Risk Prediction Model for In-Hospital Cardiac Arrest in Critically Ill Patients Using Deep Learning: Retrospective Study. JMIR Med Inform. 2020 Mar 18;8(3):e16349. doi: 10.2196/16349. PMID: 32186517; PMCID: PMC7113801. (Year: 2020) (herein NPL1), further in view of Moorman et al. (hereinafter, Moorman, US 2016/0143594).
As per claim 6, Krishnamurti further discloses, wherein:
a group is associated with predefined data related to an addiction disorder or to the intake of an addiction disorder limiting product ([0056, 0057]),
However, Krishnamurti and NPL1 do not explicitly disclose, however,
Moorman, an analogous art, teaches
a group is associated with predefined data relating to a breathing disorder or to the intake of a breathing disorder limiting product ([0068, 0070, 0096]),
a group is associated with predefined data relating to a neurological disorder or the intake of a neurological disorder limiting product ([0067, 0069, 0070]),
a group is associated with predefined data related to a cancer disorder or to the intake of a cancer disorder limiting product ([0187]),
a group is associated with predefined data related to an aging disorder or to the intake of an aging disorder limiting product ([0187]), and
a group is associated with predefined data related to a cardiac disorder or the intake of a cardiac disorder limiting product ([0096, 0098]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Krishnamurtia and NPL1 to include “ disease-specific characteristics collected from large, clinically well-annotated databases during health and illness”, taught by Moorman. One would be motivated to do this in order to perform analysis work for clarifying and predicting a patient’s sudden death possibility.
Claim 7-9 are rejected under 35 U.S.C. 103 as being unpatentable over Krishnamurti et al. (herein Krishnamurti, US 2020/0051697), in view of
NPL1--Kim J, Park YR, Lee JH, Lee JH, Kim YH, Huh JW. Development of a Real-Time Risk Prediction Model for In-Hospital Cardiac Arrest in Critically Ill Patients Using Deep Learning: Retrospective Study. JMIR Med Inform. 2020 Mar 18;8(3):e16349. doi: 10.2196/16349. PMID: 32186517; PMCID: PMC7113801. (Year: 2020) (herein NPL1), further in view of NPL2, L. Vanitha, G. R. Suresh and C. JenefarSheela, "Sudden Cardiac Death prediction system using Hybrid classifier," 2014 International Conference on Electronics and Communication Systems (ICECS), Coimbatore, India, 2014, pp. 1-5, doi: 10.1109/ECS.2014.6892677. (Herein, NPL2)
As per claim 7, Krishnamurti further discloses,
however, Krishnamurti and NPL1 do not explicitly disclose,
wherein the groups are obtained by applying a k-means partitioning technique on a set of data comprising data related to the care pathway of a set of patients and each predefined data of a group is obtained by applying a language analysis tool on a set of data comprising data related to the care pathway of the set of patients.
NPL2 teaches (see Abstract).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Krishnamurtia and NPL1 to include “clustering patient data into groups”, taught by NPL2. One would be motivated to do this in order to perform analysis work for clarifying and predicting a patient’s sudden death possibility.
As per claim 8, Krishnamurti further discloses,
wherein the set of data includes 15 artificial data generated by applying a function to data relating to the care pathway of a set of patients ([0019, 0025, 0054, 0056, 0058, 0079, 0080, Table 1]).
As per claim 9, Krishnamurti further discloses, however, Krishnamurti does not explicitly disclose, wherein the function is an adversarial neural network. 20.
NPL1 teaches (P.2, Given the complexity and time dependency of ICU data, machine learning–based methods including the deep learning–based early warning system and gradient boosting machine have provided a good basis to develop risk prediction
models using large clinical data contained within electronic medical records [8-12]. Specifically, several deep neural network algorithms have been applied to develop an early warning system for cardiac arrest to predict IHCA a few hours before
the event)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Krishnamurti to include “neural network”, taught by NPL1. One would be motivated to do this in order to perform analysis work for clarifying and predicting a patient’s sudden death possibility.
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Burton (US 2007/0032733, teaches detecting sleep disordered breathing (SDB), cardiac events and/or heart rate variability (HRV) in a subject from a physiological electrocardiogram (ECG) signal).
Schaeffer et al. (US 2022/0044826, facilitates the discovery of insights of therapeutic significance, through the automated analysis of patterns occurring in patient clinical, molecular, phenotypic, and response data, and enabling further exploration via a fully integrated, reactive user interface).
Sirendi et al. (US Patent 11,497,430, teaches analyzing cardiac data relating to a patient).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SUN M LI whose telephone number is (571)270-5489. The examiner can normally be reached on Mon-Thurs, 8:30am--5pm. Fax is 571-270-6489.
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/SUN M LI/Primary Examiner, Art Unit 3685
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