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 .
DETAILED ACTION
Response to Amendment
In the Amendment dated 06 July 2026, the following occurred:
Claims 1, 2, 9-11, and 14 were amended.
Claims 2, 9, 12, and 13 were canceled.
Claims 1-7, 10, 11, and 14-20 are pending.
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 1-7, 10, 11, and 14-20 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.
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
The claims recite a system for patient stratification and therefore meet step 1.
Step 2A1
The limitations of (Claim 1) …determining a conformity metric indicative of a similarity between clinical data of a patient and one or more conformal sets; in response to the conformity metric satisfying a second threshold, determin[ing], based at least on the clinical data of the patient, a risk score for the patient; in response to the risk score for the patient exceeding a first threshold, …determin[ing] a first probability of the risk score being a false positive; in response to the risk score for the patient failing to exceed the first threshold, …determin[ing] a second probability of the risk score being a false negative…; determining an uncertainty associated with the risk score of the patient; and determining one or more clinical recommendations for the patient…, the uncertainty associated with the risk score, the first probability of the risk score being the false positive, a contextual information for the patient, and the second probability of the risk score being the false negative…, and wherein the uncertainty… is determined by at least applying a Monte Carlo dropout to assess a change in the risk score caused by ignoring an output of one or more layers…, as drafted, is a process that, under the broadest reasonable interpretation, falls in the grouping of certain methods of organizing human activity (i.e., managing personal behavior including following rules or instructions).
That is, other than reciting a system implemented by at least one data processor and at least one memory, the claimed invention amounts to managing personal behavior or interaction between people. For example, but for the data processor/memory, this claim encompasses a person analyzing risk score data to determine probabilities of false positives and false negatives in the manner described in the identified abstract idea, supra. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or interactions between people but for the recitation of generic computer components, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Step 2A2
This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of at least one data processor and at least one memory that implement the identified abstract idea. The processor/memory is not exclusively described by the applicant and is recited at a high-level of generality (i.e., generic computer components) such that it amounts no more than mere instructions to apply the exception using a generic computer or components thereof. 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 further recites the additional elements of using first, second, and third machine learning models comprising feed forward neural networks and a decision tree to determine and analyze the risk scores. This represents mere instructions to implement the abstract idea on a generic computer. Implementing an abstract idea using a generic computer or components thereof does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. See, e.g., Recentive Analytics, Inc. v. Fox Corp., No. 2023-2437 at 10 (Fed. Cir. April 18, 2025) (finding that claims that do no more than apply established methods of machine learning to a new data environment are ineligible). Alternatively, or in addition, the implementation of the machine learning models to the clinical data merely confines the use of the abstract idea (i.e., the trained models) to a particular technological environment or field of use (the noted types of ML) and thus fails to add an inventive concept to the claims. 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
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform the noted steps amounts to no more than mere instructions to apply the exception using a generic computer component cannot provide an inventive concept (“significantly more”).
As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of first, second, and third machine learning models and a decision tree were determined to represent “apply it” on a generic computer. This has been re-evaluated under the “significantly more” analysis and has also been found insufficient to provide significantly more. MPEP 2106.05(I)(A) indicates that merely saying “apply it” or equivalent to the abstract idea cannot provide an inventive concept (“significantly more”). Further, and for completeness, the prior art of record indicates that using a feed forward neural network is well-understood, routine, conventional activity in the field (see Brewer et al., US 7020521 at Col. 19, Line 29-36; Baker, US 2021/0342683 at Para. 0027; Malkosh et al., US 2022/0138383). Accordingly, even in combination, these additional elements do not provide significantly more. As such the claim is not patent eligible.
Claims 2-7, 10, 11, and 14-20 are similarly rejected because they either further define/narrow the abstract idea and/or do not further limit the claim to a practical application or provide an inventive concept such that the claims are subject matter eligible even when considered individually or as an ordered combination.
Claim 2 merely describes rejecting clinical data, which further defines the abstract idea.
Claim 3 merely describes encoding the clinical data and determining the conformity metric, which further defines the abstract idea.
Claim 4 merely describes the conformity metric, which further defines the abstract idea.
Claims 5 and 6 merely describe the one or more conformal sets, which further defines the abstract idea.
Claim 7 merely describes the first probability of the risk score being the false positive and the second probability of the risk score being the false negative, which further defines the abstract idea.
Claims 10 and 11 merely describe the uncertainty, which further defines the abstract idea.
Claims 14-16 merely describe the one or more clinical recommendations, which further defines the abstract idea.
Claim 17 merely describes the one or more additional labs, which further defines the abstract idea.
Claim 18 merely describes the set of most important features, which further defines the abstract idea.
Claim 19 merely describes determining a measured clinical outcome, determining an expected clinical outcome, and determining an adjustment, which further defines the abstract idea.
Claim 20 merely describes decomposing the difference and determining the adjustment, which further defines the abstract idea.
Response to Arguments
Rejection under 35 U.S.C. § 101
Regarding the rejection of Claims 1-7, 10, 11, and 14-20, the Examiner has considered the Applicant’s arguments; however, the arguments are not persuasive. Any arguments inadvertently not addressed are unpersuasive for at least the following reasons. Applicant argues:
Amended claim 1 is not directed to “managing personal behavior or interaction between people.” …claim 1 recites a specific, technical machine-learning architecture for patient stratification…
Regarding (a), the Examiner respectfully disagrees. There is no specific architecture claimed; using multiple machine learning models does not describe the “architecture” of a model; it merely describes the number of models. Further, the neural networks used by the claim are described as feed forward neural networks, which, even assuming they represent extra-solution activity, are well-understood, routine, and conventional in the art as evidenced by the prior art of record.
The noted architecture solves a specific technical problem in the field of clinical decision support systems—high false-alarm rates leading to alarm fatigue and missed interventions—by providing a multi-pronged, uncertainty-aware stratification workflow. Claim 1 thus imposes meaningful limits on practicing any abstract idea and improves the functioning of a computer-implemented medical diagnostic system.
Regarding (b), the Examiner respectfully disagrees. The listed problem is a problem related to the data or how the data is analyzed (the abstraction). It is not a problem caused by the computer. It is a problem that exists independent of the computer and is thus not a technical problem.
…the combination of conformal analysis, conditional feed-forward neural networks, explicit uncertainty quantification, and a context-aware decision tree is not well-understood, routine, or conventional.
Regarding (c), the Examiner respectfully disagrees. MPEP 2106.05(d) states: “Another consideration when determining whether a claim recites significantly more than a judicial exception is whether the additional element(s) are well-understood, routine, conventional activities previously known to the industry (emphasis added).” Further, MPEP 2106.05(I) states: “As made clear by the courts, the novelty of any element or steps in a process, or even of the process itself, is of no relevance in determining whether the subject matter of a claim falls within the § 101 categories of possibly patentable subject matter (internal quotations omitted, emphasis original).” As such, it is only the additional elements identified by the Examiner to not be part of the abstract idea that are analyzed to determine whether they represent well-understood, routine, conventional activities in the field of the invention.
In that regard, MPEP 2106.05(d)(I) indicates that in determining whether the additional elements represent are well-understood, routine, conventional activities, the Examiner should consider whether the additional elements (1) provide an improvement to the technological environment to which the claim is confined, (2) whether the additional elements are mere instructions to apply the judicial exception, or (3) whether the additional elements represent insignificant extra-solution activity. The additional elements of the claims do not provide significantly more based on this inquiry.
Taking these in turn, whether the additional elements of the claim provide an improvement was analyzed/addressed in the 2A2 analysis. The technological environment to which the claims are confined (a general-purpose computer performing generic computer functions) is recited at a high level of generality and has been found by the courts to be insufficient to provide a practical application (see MPEP 2106.05(d)(II); Alice Corp.).
Finally, the additional element of using feed forward neural networks that was found to represent extra-solution activity was analyzed and determined to represent well-understood, routine, conventional activity in the field. As such, when viewed either individually or as an ordered combination, the additional elements do not provide significantly more to the abstract idea and the claims are not subject matter eligible.
More importantly, past machine learning model approaches suffered from high false alarm rates. Claim 1 improves machine learning technology by providing a novel machine learning architecture…
Regarding (d), the Examiner respectfully disagrees. The listed problem is a problem related to the data or how the data is analyzed (the abstraction). It is not a problem caused by machine learning technology; the machine learning will output whatever it is trained to output. The problem is in the data.
Further, MPEP 2106.04(d)(1) states “the word ‘improvements’ in the context of this consideration is limited to improvements to the functioning of a computer or any other technology/technical field, whether in Step 2A Prong Two or in Step 2B.” Here, there is no improvement to the computer nor is there an improvement to another technology. Because neither type of improvement is present in the claims, an improvement to technology is not present and there is no practical application.
Applicant’s argument that the field(s) of clinical decision support systems/machine learning is a technology, and the claimed invention improves this field is not reflected in the claimed invention. The claims are confined to a general-purpose computer and do not claim a clinical decision support system. Moreover, the entire field of clinical decision support systems/machine learning is not reasonably understood to be a problem arising in technology, as it is instead a problem arising in healthcare. The claimed invention is using a computer as a tool and any improvement present is an improvement to the abstract idea of, to paraphrase, stratifying patients. Finally, if Applicant’s line of reasoning were correct, the invention in Alice Corp. would have been subject matter eligible because it was an improvement to the technology of settlement risk mitigation.
Conclusion
Prior art made of record though not relied upon in the present basis of rejection are noted in the attached PTO 892 and include:
Crabtree et al. (U.S. 2025/0175456) which discloses a network for threat mapping and characterization and risk adjusted response.
Levi et al. (U.S. 11328400) which discloses a method and system for computer-aided aneurysm triage.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CAMRYN B LEWIS whose telephone number is (703)756-1807. The examiner can normally be reached Monday - Friday, 11:00 am - 8:00 pm EST.
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/CAMRYN B LEWIS/
Examiner, Art Unit 3683
/JASON S TIEDEMAN/Primary Examiner, Art Unit 3683
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