CTFR 18/940,249 CTFR 94166 DETAILED ACTION 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. 12-151 AIA 26-51 12-51 Status of Claims This Final Office Action is in response to the Amendment and Remarks filed 02/13/2026. Claims 1, 5, 9-11, 15-16 and 18-20 are currently pending and considered herein. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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, 5, 9-11, 15-16 and 18-20 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 recites as follows, wherein the abstract elements are not emboldened: A computing device, comprising: one or more processors; and one or more computer-readable media that collectively store instructions that, when executed by the one or more processors, cause the computing device to perform operations , the operations comprising: obtaining demographic data of a user, the demographic data comprising an age for the user; obtaining physiological data of the user from one or more physiological sensors , the physiological data comprising one or more cardiac metrics of the user; inputting the demographic data and the physiological data into a machine-learned model configured to output a predicted cardiac age for the user using at least the demographic data and the physiological data as model inputs; generating a cardiac score based on the predicted cardiac age output by the machine-learned model and the age for the user, the cardiac score configured to assess cardiac health of the user; obtaining at least one of historical activity data for the user and one or more activity preferences for the user; determining a recommended activity for the user based on the cardiac score and the at least one of the historical activity data for the user and the one or more activity preferences for the user, wherein the recommended activity is configured to influence the cardiac score of the user to achieve a desired cardiac score; prompting the user to perform the recommended activity in response to a trigger; determining an updated cardiac score based on inputting the demographic data and updated physiological data of the user to the machine-learned model, wherein the updated physiological data is obtained from the one or more physiological sensors while the user performs the recommended activity; and causing a display screen of the computing device to display a comparison of the cardiac score and the updated cardiac score so as to indicate to the user an influence of the recommended activity on the one or more cardiac metrics and the cardiac score. Independent claims 11 and 20 recite substantially similar limitations. The above limitations of “obtaining demographic data of a user, the demographic data comprising an age for the user; obtaining physiological data of the user, the physiological data comprising one or more cardiac metrics of the user; inputting the demographic data and the physiological data into a model configured to output a predicted cardiac age for the user using at least the demographic data and the physiological data as model inputs; generating a cardiac score based on the predicted cardiac age output by the model and the age for the user, the cardiac score configured to assess cardiac health of the user; obtaining at least one of historical activity data for the user and one or more activity preferences for the user; determining a recommended activity for the user based on the cardiac score and the at least one of the historical activity data for the user and the one or more activity preferences for the user, wherein the recommended activity is configured to influence the cardiac score of the user to achieve a desired cardiac score; prompting the user to perform the recommended activity in response to a trigger; determining an updated cardiac score based on inputting the demographic data and updated physiological data of the user to the model, wherein the updated physiological data is obtained while the user performs the recommended activity; and causing a comparison of the cardiac score and the updated cardiac score so as to indicate to the user an influence of the recommended activity on the one or more cardiac metrics and the cardiac score,” as drafted, is a process that, under its broadest reasonable interpretation, is an abstract idea that covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than broadly reciting “a computing device, comprising: one or more processors; and one or more computer-readable media that collectively store instructions,” “physiological sensors,” a “machine-learned model” and “causing a display screen of the computing device to display,” nothing in the claim elements precludes the steps from practically being performed in the mind. For example, but for the generic computer components, sensors, machine-learned model and display, a computer-implemented method or system, in the context of this claim, encompasses one skilled in the pertinent art to manually determine a predicted cardiac age and/or score based on health and physiological data of the patient and to provide recommendations of an activity and monitor patient performance of the activity. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Additionally, the claims recite the abstract idea of a form of organizing human activity including following rules or instructions, and broadly amounts to interactions between a physician observing and diagnosing her patients, making recommendations then recording observations and influencing the patient. The claims appear to monopolize the diagnostic techniques of the physician making clinical assessments concerning patient cardiac data/health and other patient data and influencing a patient to perform prompted activities. Accordingly, the claims recite an abstract idea. This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements “a computing device, comprising: one or more processors; and one or more computer-readable media that collectively store instructions,” “physiological sensors,” a “machine-learned model” and “causing a display screen of the computing device to display.” However, the use of a computer, machine-learned model, sensors and display in these steps are recited at a high-level of generality ( i.e. , as a generic processor/server/storage/display performing a generic computer function of receiving inputs, analyzing the inputs, and displaying selected information) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements when considered separately and as an ordered combination do not integrate the judicial exception/abstract idea into a “practical application” of the judicial exception because they do not impose any meaningful limit on practicing the judicial exception. The claim is thus directed to an abstract idea. 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 elements of “a computing device, comprising: one or more processors; and one or more computer-readable media that collectively store instructions,” “physiological sensors,” a “machine-learned model” and “causing a display screen of the computing device to display,” amounts to no more than mere instructions to apply the exception using a computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The dependent claims do not remedy the deficiencies of the independent claims with respect to patent eligible subject matter. The dependent claims further limit the abstract idea Claims 5 and 15 detail additional patient data and a machine-learned model which is recited at a high level of generality and comprises mere instructions to apply the exception using a computer component. Even in combination, the machine-learned model does not illustrate a practical application or comprise significantly more than the abstract idea. Claims 6-7 and 16-17 include additional data for including in a cardiac score including physiological data, and further limits the abstract idea. Claims 9 and 19 describe a heart rate and limit the abstract idea. Claims 8 and 18 recite a second model which is recited at a high level of generality and comprises mere instructions to apply the exception using a computer component. Even in combination, the second model does not illustrate a practical application or comprise significantly more than the abstract idea. Claim 10 includes a wearable computing device or mobile computing device, which are recited at a high level of generality and are mere instructions to apply the exception using a computer component and cannot provide an inventive concept. Thus, the additional limitations from dependent claims merely detail a type of data input or calculated from one source or another, and limits the abstract idea. Therefore, claims 1, 5, 9-11, 15-16 and 18-20 are not patent eligible. Response to Arguments Applicant’s remarks filed on February 13, 2026 have been fully considered, but they are not entirely persuasive. The following explains why: Applicant’s arguments pertaining to prior art rejections are persuasive. The rejection with regard to the 35 U.S.C. §103 has been withdrawn. The arguments pertaining to prior art references of the Applicant’s Remarks are persuasive. The closest prior art that relates to the amended claims includes U.S. 11,056,242 B1 to Jain (Claim 1), U.S. 2025/0248607 A1 to Vakili, U.S. 2021/0361217 A1 to Attia, and U.S. 2024/0194344 A1 to Capodilupo. However, the prior art fails to disclose alone or in combination, as claimed in the independent claims: determining a recommended activity for the user based on the cardiac score and the at least one of the historical activity data for the user and the one or more activity preferences for the user; determining an updated cardiac score based on inputting the demographic data and updated physiological data of the user to the machine-learned model, wherein the updated physiological data is obtained from the one or more physiological sensors while the user performs the recommended activity; and causing a display screen of the computing device to display a comparison of the cardiac score and the updated cardiac score so as to indicate to the user an influence of the recommended activity on the one or more cardiac metrics and the cardiac score. Applicant’s arguments pertaining to subject matter eligibility are not persuasive. The basis for the previous rejection under 35 U.S.C. §101 is still operative and the claims have been addressed with regard to the updated 35 U.S.C. §101 rejection discussed above, and considered under the relevant sections of the MPEP. The arguments at pages 8-12 of Applicant’s Remarks are not persuasive. At pages 8-12 the Examiner disagrees that there is not an abstract idea. The Examiner disagrees there is a practical application or significantly more than the abstract idea. Moreover, there is no clear technological improvement in the claims to a technological problem. The claims describe a mental process. That it may be tedious or laborious to perform analyses in the mind or manually is not of consequence in the eligibility analysis. The claims also describe organizing human activity as following rules or instructions, as detailed above. In addition, the Examiner respectfully disagrees with arguments at Pages 9-10 that the claims are akin to Example 39 of the 2019 PEG as argued by Applicant. However, here the machine-learned model is just a computer tool used to employ the abstract idea. The ML model in the claims is recited at a high level, and amount to applying the exception using a generic computer (see e.g. Updated PEG Example 47, claim 2, where the “detecting” and “analyzing” were mental processes, and “using the trained ANN” amounted to generic computer implementation, as is the case for the claimed neural network and training and configuration to “classify a free text string relating to a route of administration to a route of administration code based on the plurality of output layers . ” Mere instructions to apply an exception using a generic computer component/implementation cannot provide an inventive concept. Furthermore, the Examiner disagrees with the arguments at Pages 11-12. The PTAB explained in Ex parte Hannun , hypothetically , that if the claims recited an exception, the claims recited a practical application because “the claims of the current application include specific features that were specifically designed to achieve an improved technological result” and “provide improvements to that technical field.” However, unlike Ex parte Hannun , the instant claims lack the requisite specificity, for example, the additional element of the ML model and the recitations of being updated (trained) by inputting demographic and updated physiological data of the user, and then updating the cardiac score are results based in nature and do not include details as to how the machine-learned model or the updating of it is done beyond known functions or how there are any improvements to that technical field. Improving the accuracy of a model by feeding it better data does not constitute an improvement to the model, but rather to the choice in data input. Accordingly, the claims recite an abstract idea. For at least these reasons and those stated above, the claims are not patent eligible. Conclusion 07-39 AIA 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 WILLIAM T. MONTICELLO whose telephone number is (313)446-4871. The examiner can normally be reached M-Th; 08:30-18:30 EST. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, FONYA LONG can be reached at (571) 270-5096. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /WILLIAM T. MONTICELLO/Examiner, Art Unit 3682 /FONYA M LONG/Supervisory Patent Examiner, Art Unit 3682 Application/Control Number: 18/940,249 Page 2 Art Unit: 3682 Application/Control Number: 18/940,249 Page 3 Art Unit: 3682 Application/Control Number: 18/940,249 Page 4 Art Unit: 3682 Application/Control Number: 18/940,249 Page 5 Art Unit: 3682 Application/Control Number: 18/940,249 Page 6 Art Unit: 3682 Application/Control Number: 18/940,249 Page 7 Art Unit: 3682 Application/Control Number: 18/940,249 Page 8 Art Unit: 3682 Application/Control Number: 18/940,249 Page 9 Art Unit: 3682 Application/Control Number: 18/940,249 Page 10 Art Unit: 3682 Application/Control Number: 18/940,249 Page 11 Art Unit: 3682 Application/Control Number: 18/940,249 Page 12 Art Unit: 3682
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