DETAILED ACTION
Response to Amendment
This action is in response to the amendment filed on November 24, 2025. Claims 1, 10, and 19-20 have been amended. Claims 1-20 have been examined and are currently pending.
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 .
Inventorship
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
ALICE/ MAYO: TWO-PART ANALYSIS
2A. First, a determination whether the claim is directed to a judicial exception (i.e., abstract idea).
Prong 1: A determination whether the claim recites a judicial exception (i.e., abstract idea).
Groupings of abstract ideas enumerated in the 2019 Revised Patent Subject Matter Eligibility Guidance.
Mathematical concepts- mathematical relationships, mathematical formulas or equations, mathematical calculations.
Certain methods of organizing human activity- fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions).
Mental processes- concepts performed in the human mind (including an observation, evaluation, judgement, opinion).
Prong 2: A determination whether the judicial exception (i.e., abstract idea) is integrated into a practical application.
Considerations indicative of integration into a practical application enumerated in the 2019 Revised Patent Subject Matter Eligibility Guidance.
Improvement to the functioning of a computer, or an improvement to any other technology or technical field
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition
Applying the judicial exception with, or by use of a particular machine.
Effecting a transformation or reduction of a particular article to a different state or thing
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception
Considerations that are not indicative of integration into a practical application enumerated in the 2019 Revised Patent Subject Matter Eligibility Guidance.
Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea.
Adding insignificant extra-solution activity to the judicial exception.
Generally linking the use of the judicial exception to a particular technological environment or field of use.
2B. Second, a determination whether the claim provides an inventive concept (i.e., Whether the claim(s) include additional elements, or combinations of elements, that are sufficient to amount to significantly more than the judicial exception (i.e., abstract idea)).
Considerations indicative of an inventive concept (aka “significantly more”) enumerated in the 2019 Revised Patent Subject Matter Eligibility Guidance.
Improvement to the functioning of a computer, or an improvement to any other technology or technical field
Applying the judicial exception with, or by use of a particular machine.
Effecting a transformation or reduction of a particular article to a different state or thing
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception NOTE: The only consideration that does not overlap with the considerations indicative of integration into a practical application associated with step 2A: Prong 2.
Considerations that are not indicative of an inventive concept (aka “significantly more”) enumerated in the 2019 Revised Patent Subject Matter Eligibility Guidance.
Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea.
Adding insignificant extra-solution activity to the judicial exception.
Generally linking the use of the judicial exception to a particular technological environment or field of use.
Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. NOTE: The only consideration that does not overlap with the considerations that are not indicative of integration into a practical application associated with step 2A: Prong 2.
See also, 2019 Revised Patent Subject Matter Eligibility Guidance; Federal Register; Vol. 84, No. 4; Monday, January 7, 2019
Claims 1-20 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.
1: Statutory Category
Applicant’s claimed invention, as described in independent claim 1 is directed to a method, independent claim 10 is directed to a system and independent claim 19 is directed to a nontransitory computer readable medium.
2(A): The claim(s) are directed to a judicial exception (i.e., an abstract idea).
PRONG 1: The claim(s) recite a judicial exception (i.e., an abstract idea).
Mathematical concepts
Independent claims 1, 10, and 19 recite the limitations, “identifying a subset of the pairs of the respective ones of the plurality of medical entities that satisfy a relationship strength threshold; generating uncommonality scores for one or both of a first and a second medical entity in each of the subset of pairs, the uncommonality score for the first medical entity being indicative of a frequency that the first medical entity occurs with the second medical entity across an entire set of instances of the second medical entity in the clinical information, the uncommonality score for the second medical entity being indicative of a frequency that the second medical entity occurs with the first medical entity across an entire set of instances of the first medical entity in the clinical information; and generating a relevance score for each of the subset of pairs based on one or both of the uncommonality scores for the first and second ones of the medical entities included in the respective pair and a frequency of occurrence of the respective pair in the clinical information; and generating, by the one or more processors, a knowledge graph data structure representing ones of the subset of pairs having relevance scores, respectively, that satisfy a relevance threshold.” are directed to the abstract idea of mathematical concepts. In particular, the limitations recite using mathematical relationships, mathematical formulas, and mathematical calculations to measure a relationship strength between two medical entities, generate uncommonality scores for one or more medical entities, and a relevance score for a pair of medical entities.
PRONG 2: The judicial exception (i.e., an abstract idea) is not integrated into a practical application.
The applicant has not shown or demonstrated any of the requirements described above under "integration into a practical application" under step 2A. Specifically, the applicant's limitations are not "integrated into a practical application" because they are adding words "apply it" with the judicial exception, or mere instructions to implement an abstract idea merely as a tool to perform an abstract idea (see MPEP 2106.05(f)). Additionally, improvements to the functioning of a computer or any other technology or technical field has not been shown or disclosed (see MPEP 2106.05(a)). The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Specifically, the applicant’s limitations are not “significantly more” because they are adding words “apply it” with the judicial exception, or mere instructions to implement an abstract idea merely as a tool to perform an abstract idea (see MPEP 2106.05(f)). The applicant’s claimed limitations do not demonstrate an improvement to another technology or technical field, an improvement to the functioning of the computer itself, effecting a transformation or reduction of particular article to a different state or thing. The current application does not amount to 'significantly more' than the abstract idea as described above. The claim does not include additional elements or limitations individually or in combination that are sufficient to amount to significantly more than the judicial exception. Specifically, the individual elements of one or more processors, memory, computer readable program code, and one or more non-transitory computer readable storage media amount to no more than implementing an idea with a computerized system and they are adding words “apply it” with the judicial exception, or mere instructions to implement an abstract idea merely as a tool to perform an abstract idea. The additional elements taken in combination add nothing more than what is present when the elements are considered individually. Therefore, based on the two-part Alice Corp. analysis, there are no meaningful limitations in the claims that transform the exception (i.e., abstract idea) into a patent eligible application.
Dependent claims 2-9, 11-18, and 20 are rejected as ineligible subject matter under 35 U.S.C. 101 based on a rationale similar to the claims from which they depend. The following dependent claims: dependent claims 3, 8, 12, and 17 recite one or more processors. Dependent claims 3, 8, 12, and 17 do not recite additional elements that amount to significantly more than the judicial exception.
Since the claim(s) recite a judicial exception and fails to integrate the judicial exception into a practical application, the claim(s) is/are “directed to” the judicial exception. Thus, the claim(s) must be reviewed under the second step of the Alice/ Mayo analysis to determine whether the abstract idea has been applied in an eligible manner.
2(B): The claims do not provide an inventive concept (i.e., The claim(s) do not include additional elements, or combinations of elements, that are sufficient to amount to significantly more than the judicial exception (i.e., abstract idea)).
As discussed with respect to Step 2A Prong Two, the additional element(s) in the claim amounts to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
For these reasons, there is no invention concept in the claim, and thus the claim is ineligible.
Allowable Subject Matter
The following is a statement of reasons for the indication of allowable subject matter:
generating, by the one or more processors, a knowledge graph data structure representing ones of the subset of pairs having relevance scores, respectively, that satisfy a relevance threshold;
Response to Arguments
Applicant's arguments filed November 24, 2025 have been fully considered but they are not persuasive.
According to applicant’s argument on pages 12-15 of the remarks disclose, “While Applicant does not concede that any previously pending claims fail to recite patent-eligible subject matter, Applicant has nonetheless further amended the claims to advance prosecution. At a minimum, the amended claims integrate any abstract idea allegedly recited in the claims into a practical application under Step 2A, Prong 2 of the Alice/Mayo test…The use of a computer system to denoise a medical data set such that accurate medical relationships may then be inferred is a technical solution to the technical problem of how to accurately "build a healthcare knowledge graph based on electronic health records." Applicant's specification at paragraph [0002]. Medical information in electronic health records generally "lack[s] a definitive mapping." Id. When electronic health records lack definitive mappings, the data set is considered noisy. Noisy data sets include data that may be irrelevant or erroneous, and using knowledge graphs generated from noisy data sets may lead to incorrect results. For example, many patients receive a flu shot each year, but this treatment is almost wholly unrelated to other treatments or drugs a patient may receive. See Applicant's specification at paragraph [0041]. If a knowledge graph fails to accurately represent those relationships (e.g., indicates a correlation between getting a flu shot and having an unrelated treatment), then use of that knowledge graph (e.g., by a clinical decision support (CDS) systems) could result in an inaccurate treatment or prescription recommendation for a patient…At least the elements of "generating ... a first data set containing a plurality of medical entities" by "extracting, using a Natural Language Processing (NLP) model ... medical entities from ... clinical information", "generating ... a second data set by denoising the first data set'),"generating ... a knowledge graph structure" of the denoised data set, "storing ... the knowledge graph structure in memory', and "accessing ... the knowledge graph data structure to draw inferences of medical entity relationships" present a technical solution to the above recited technical problem associated with using knowledge graphs generated from noisy records. In particular, by not only generating a first data set that contains medical entities, but also denoising that data set to generate a second (denoised) data set, the knowledge graph is constructed in a manner that is less likely to suffer from the above-noted deficiencies, and use of the stored knowledge graph is less likely to provide erroneous or inconclusive results. Thus, claim 1 recites elements that present a technical solution to the technical problem associated with generating and using knowledge graphs…. Thus, the independent claims recite a specific denoising process that, when used to generate a knowledge graph that is in turn accessed to draw inferences of medical entity relationships, overcomes the above-noted technical problems with conventional techniques.” The examiner respectfully disagrees.
Under the 2019 Revised Patent Subject Matter Eligibility Guidance, determining whether a claim integrates a judicial exception into a practical application, examiners should consider whether the claimed invention pertains to an improvement in the functioning of the computer itself or any other technology or technical field. Additionally, making this determination, examiners should determine whether there is a technical explanation as to how to implement the invention in the specification and the claim itself reflects the improvement in technology. The recited claims do not recite and reflect an improvement in the technology or technical field as required in the 2019 Revised Patent Subject Matter Eligibility. Specifically, the applicant cites improvements such as a computer system to denoise medical data set such that accurate medical relationships may be inferred and how to accurately build healthcare knowledge graph based on noisy electronic records. These features are not recited within the body of independent claims 1, 10, and 19. Additionally, the applicant relies on paragraphs 0002 and 0041 of the applicant’s specification for claiming and explaining an improvement in the computer function and technical field. Paragraph 0002 of the applicant’s specification discloses, “…Construction of a knowledge graph for a health care application, however, may be challenging due to a lack of a representative knowledge graph construction taxonomy. Example healthcare related knowledge graphs may be built by humans with domain knowledge of healthcare, but such a build approach may be slow and costly. Attempts to build a healthcare knowledge graph based on electronic health records associated with patients have been met with challenges due to the lack of a definitive mapping between clinical medical entities, such as drugs, diagnoses, procedures, and the like. For example, even though Drug A and Drug B appear in the same electronic health record, it may not be clear how these two drugs are related. Also, the appearance of Drug A and Disease C in an electronic health record does not necessarily mean that Drug A is being used to treat Disease C. A patient's chart or health record often includes multiple types of symptoms, diagnoses, and drugs. These vague relationships may make it difficult to build knowledge graphs from electronic health records.” Paragraph 0041 of the applicant’s specification discloses, “Advantageously, a knowledge graph configured in the non-transitory computer readable medium may provide an information dense compilation of health care information that is efficiently accessible using one or more processors in a variety of healthcare applications including, but not limited to, predictive modeling of diseases, care regiments, claim generation, and the like. Moreover, the accuracy of the knowledge graph may be improved by filtering out those medical entity relationships based on high frequency medical entities that are unlikely to have a relevant relationship with many or most other medical entities, e.g,, many patients receive a flu shot, but this medication is mostly unrelated to other treatments or drugs the patients receive.” Paragraph 0002 discloses the challenges associated with creating a knowledge graph for healthcare applications and challenges associated with mapping between clinical medical entities. Paragraph 0041 discloses accuracy of knowledge graph can be improved by filtering medical entity relationships. The cited paragraphs 0002 and 0041 and the entire applicant’s specification do not provide a technical explanation as to how the invention/computer, technical field, or other technology is improved with regards to a computer system to denoise medical data set such that accurate medical relationships may be inferred and how to accurately build healthcare knowledge graph based on noisy electronic records. Additionally, the applicant's arguments are geared towards the intended end result of a computer system to denoise medical data set such that accurate medical relationships may be inferred and how to accurately build healthcare knowledge graph based on noisy electronic records, but not how the improvement is performed or implemented. The examiner notes the implementation or use of machine learning/natural language processing model does not automatically describe an improvement in the computer itself, technology, or technical field. In particular, denoising data or a data set using a natural language processing model is not an improvement in the technology because the cleansing of data or a data set is an activity that is performed or required prior to further analysis of the data or data set. Further, the denoising process utilizes mathematical concepts to arrive at relationships between or among medical entities, which is not an improvement in the technical field or computer functions. Therefore, the examiner maintains the rejection.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Jain et al. US Patent 11,901,083 B1 Using Genetic and Phenotypic Data Sets for Drug Discovery Clinical Trials
Jain discloses “In other implementations, a knowledge graph can be used instead, or in additional to, a machine learning system. FIG. 6 shows an example knowledge graph 600. The system 100 can generate the knowledge graph 600 based on the genetic data, the health data, and the epigenetic data of users. The knowledge graph is a set of tuples that specify nodes connected by relations. The knowledge graph 600 includes a health risk node 602 (e.g., hypertension) connected by a node representing comorbidity and nodes representing factors increasing or decreasing the health risk. The comorbidity node 604 includes conditions/diseases linked to the health risk node 602, e.g., hyperuricemia 604a to dyslipidemia 604n. The increased risk node 606 includes factors 606a-606n that contribute to the increased risk of the health risk (e.g., in this case, hypertension). The decreased risk node 608 includes factors 608a-608n that contribute to the decreased risk of the health risk. The system can learn adequate thresholds to use for each factor to classify into the increased risk and the decreased risk. For example, the system determines that age less than 30 is linked to decreased risk for hypertension, based on scientific findings (e.g., literature support). While discrete categories are shown for increased or decreased risk, in some implementations, the system quantifies the risk at a granular level (e.g., with a score or percentage, such as 40% increased risk for hypertension; or with a category of risk, such as high, medium, low, etc.). For example, the system can combine how many of risk factors the user has and determines the risk based on the weighted average (e.g., equal weighting of factors 606a-606n). The knowledge graph 600 can be stored in the database 148 or a separate database other than the database 148.” (column 40, line 61 to column 41, line 25).
THIS ACTION IS MADE FINAL. 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW L HAMILTON whose telephone number is (571)270-1837. The examiner can normally be reached Monday-Thursday 9:30-5:30 pm EST.
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/MATTHEW L HAMILTON/Primary Examiner, Art Unit 3682