Prosecution Insights
Last updated: April 19, 2026
Application No. 17/946,117

MACHINE LEARNING MODELS FOR AUTOMATED SELECTION OF EXECUTABLE SEQUENCES

Final Rejection §101§103
Filed
Sep 16, 2022
Examiner
KEATON, SHERROD L
Art Unit
2148
Tech Center
2100 — Computer Architecture & Software
Assignee
Evernorth Strategic Development Inc.
OA Round
2 (Final)
52%
Grant Probability
Moderate
3-4
OA Rounds
4y 6m
To Grant
88%
With Interview

Examiner Intelligence

Grants 52% of resolved cases
52%
Career Allow Rate
295 granted / 563 resolved
-2.6% vs TC avg
Strong +36% interview lift
Without
With
+36.1%
Interview Lift
resolved cases with interview
Typical timeline
4y 6m
Avg Prosecution
32 currently pending
Career history
595
Total Applications
across all art units

Statute-Specific Performance

§101
14.9%
-25.1% vs TC avg
§103
62.0%
+22.0% vs TC avg
§102
11.1%
-28.9% vs TC avg
§112
8.0%
-32.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 563 resolved cases

Office Action

§101 §103
DETAILED ACTION This action is in response to the filing of 11-3-2025. Claims 1-2, 4-13 and 15-20 are pending and have been considered below: 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 1-2, 4-13 and 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Step 1: Claims 1-2, 4-13 and 15-20 represent system and method type claims. Therefore claims 1-20 are directed to either a process, machine, manufacture or composition of matter. Regarding claim 1: 2A Prong 1: generating a feature vector input based on the structured input data; generating a subset of fall-influencing classification codes by selecting a subset of the healthcare classification codes whose corresponding predictive models exceed a performance threshold or rank among top-performing models: and representing at least one of the fall-influencing classification codes as a feature of the set of features; As drafted, under the broadest reasonable interpretation, the claim covers mental processes (concepts performed in the human mind including an observation, evaluation, judgment, opinion-a user can generate a codes and feature vector) and processing, by the machine learning model, the feature vector input to generate an entity fall likelihood output, wherein the entity fall likelihood output indicates a likelihood that the entity will experience a fall based on the feature vector input; As drafted, under the broadest reasonable interpretation, the claim covers mental processes (concepts performed in the human mind including an observation, evaluation, judgment, opinion-a user can generate a output) determining a subset of the multiple database entities having entity fall likelihood outputs that satisfy a recommendation threshold; and for each database entity in the subset: determining output impact scores for parameters of the feature vector input associated with the database entity, wherein each output impact score is indicative of an effect of the parameter on the entity fall likelihood output for the database entity; As drafted, under the broadest reasonable interpretation, the claim covers mental processes (concepts performed in the human mind including an observation, evaluation, judgment, opinion-a user can determine a subset) and generating a feature list based on the determined output impact scores, wherein the feature list is specific to the database entity and includes one or more of the parameters having the highest output impact scores. As drafted, under the broadest reasonable interpretation, the claim covers mental processes (concepts performed in the human mind including an observation, evaluation, judgment, opinion-a user can generate a list based on scoring) 2A Prong 2: This judicial exception is not integrated into a practical application. Additional elements: memory hardware configured to store a machine learning model and computer-executable instructions; and processor hardware configured to execute the instructions, wherein the instructions include:(mere instructions to apply the exception using a generic computer component) obtaining a set of multiple database entities; for each database entity in the set of multiple database entities: obtaining structured input data specific to the database entity; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) wherein a set of features of the feature vector input is based on: receiving historical data for a plurality of entities for each entity of the plurality of entities: determining whether the entity has experienced a fall; and in response to the entity having experienced a fall, identifying a set of healthcare classification codes from the historical data for the entity: performing feature reduction by generating a predictive model for each classification code of the set of healthcare classification codes and measuring performance of each predictive model in predicting a likelihood that the entity will experience a fall: (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) wherein each output impact score is indicative of an effect of the parameter on the entity fall likelihood output for the database entity; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Additional elements: memory hardware configured to store a machine learning model and computer-executable instructions; and processor hardware configured to execute the instructions, wherein the instructions include:(mere instructions to apply the exception using a generic computer component) obtaining a set of multiple database entities; for each database entity in the set of multiple database entities: obtaining structured input data specific to the database entity; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) wherein a set of features of the feature vector input is based on: receiving historical data for a plurality of entities for each entity of the plurality of entities: determining whether the entity has experienced a fall; and in response to the entity having experienced a fall, identifying a set of healthcare classification codes from the historical data for the entity: performing feature reduction by generating a predictive model for each classification code of the set of healthcare classification codes and measuring performance of each predictive model in predicting a likelihood that the entity will experience a fall: (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) wherein each output impact score is indicative of an effect of the parameter on the entity fall likelihood output for the database entity; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) Regarding claim 2: 2A Prong 1: determining whether the entity has experienced a fall; in response to the entity having experienced a fall, generating a fall training sample for the fall training dataset that includes the historical data corresponding to the entity and an indication that the entity has experienced a fall; and in response to the entity failing to experience a fall, generating a non-fall training sample for the non-fall training dataset that includes the historical data corresponding to the entity and an indication that the entity has not experienced a fall. As drafted, under the broadest reasonable interpretation, the claim covers mental processes (concepts performed in the human mind including an observation, evaluation, judgment, opinion-a user can determine a fall and generate samples) 2A Prong 2: This judicial exception is not integrated into a practical application. Additional elements: receiving historical data for a plurality of entities; and for each entity of the plurality of entities, (adding insignificant extra-solution activity to judicial exception – see MPEP 2106.05(g)) 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Additional elements: receiving historical data for a plurality of entities; and for each entity of the plurality of entities, (MPEP 2106.05(d)(II) indicate that merely “receiving or transmitting data over a network” is a well understood, routine, conventional function when it is claimed in a merely generic manner (as it is in the present claim). Thereby, a conclusion that the claimed receiving step is well-understood, routine, conventional activity is supported under Berkheimer) Regarding claim 4: 2A Prong 1: generating the subset of fall-influencing classification codes includes determining a count of each healthcare classification code from the set of healthcare classification codes for the plurality of entities that have experienced a fall. As drafted, under the broadest reasonable interpretation, the claim covers mental processes (concepts performed in the human mind including an observation, evaluation, judgment, opinion-a user can determine a count) 2A Prong 2: This judicial exception is not integrated into a practical application. No Additional elements: 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. No Additional elements: Regarding claim 5: 2A Prong 1: wherein the feature vector input combines claims data, demographic data, and lab test data for the respective database entity. As drafted, under the broadest reasonable interpretation, the claim covers mental processes (concepts performed in the human mind including an observation, evaluation, judgment, opinion-a user can combine features) 2A Prong 2: This judicial exception is not integrated into a practical application. No Additional elements: 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. No Additional elements: Regarding claim 6: 2A Prong 1: No Additional abstract ideas 2A Prong 2: This judicial exception is not integrated into a practical application. Additional elements: wherein a feature of the set of features of the feature vector input represents one or more categories of criteria indicating inappropriate medication use in adults of a particular age range. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Additional elements: wherein a set of the features of the feature vector input represents one or more categories of criteria indicating inappropriate medication use in adults of a particular age range. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) Regarding claim 7: 2A Prong 1: wherein the feature vector input combines claims data, demographic data, and lab test data for the respective database entity with the one or more categories of the criteria indicating inappropriate medication use for the respective database entity. As drafted, under the broadest reasonable interpretation, the claim covers mental processes (concepts performed in the human mind including an observation, evaluation, judgment, opinion-a user can combine features) 2A Prong 2: This judicial exception is not integrated into a practical application. No Additional elements: 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. No Additional elements: Regarding claim 8: 2A Prong 1: No Additional abstract ideas 2A Prong 2: This judicial exception is not integrated into a practical application. Additional elements: wherein the instructions further include automatically selecting an executable sequence according to the entity fall likelihood output associated with the respective database entity. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Additional elements: wherein the instructions further include automatically selecting an executable sequence according to the entity fall likelihood output associated with the respective database entity. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) Regarding claim 9: 2A Prong 1: No Additional abstract ideas 2A Prong 2: This judicial exception is not integrated into a practical application. Additional elements: wherein automatically selecting the executable sequence includes automatically scheduling a care intervention for the respective database entity. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Additional elements: wherein automatically selecting the executable sequence includes automatically scheduling a care intervention for the respective database entity. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) Regarding claim 10: 2A Prong 1: No Additional abstract ideas 2A Prong 2: This judicial exception is not integrated into a practical application. Additional elements: wherein the care intervention includes at least one of a text message intervention, an email intervention, an automated phone call intervention, and a live phone call intervention. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Additional elements: wherein the care intervention includes at least one of a text message intervention, an email intervention, an automated phone call intervention, and a live phone call intervention. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) Regarding claim 11: 2A Prong 1: No Additional abstract ideas 2A Prong 2: This judicial exception is not integrated into a practical application. Additional elements: wherein automatically selecting the executable sequence includes automatically scheduling the respective database entity to a care case management database. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Additional elements: wherein automatically selecting the executable sequence includes automatically scheduling the respective database entity to a care case management database. (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea) Claims 12-13 and 15-20 recite methods with similar limitations to claims 1-2 and 4-11, and therefore are also rejected under 101. The claims recite abstract ideas not integrated into a practical application, nor including additional elements that amount to significantly more. See analysis of claims 1-2 and 4-11. Claim Objections Claims are allowed over the prior art, but remain rejected under 35 U.S.C. 101. Claim Rejections - 35 USC § 103 Claims rejected under 35 U.S.C. 103 has been withdrawn. Response to Arguments Applicant's remarks and amendments have been considered. Regarding the 101, the action of feature reduction is a widely used form of processing data. This technique is generally used for improving a plurality of models. Utilizing a generic functionality does not provide a model improvement, tailored specifically to the improvement of predicting a fall. Feature reduction could be applied to any model in order to manage data and improve accuracy. The improvement should be explicit to this model in order to provide a technical advancement over similar models. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. 20230215568 A1 KUMAR ET AL. 20170213145 A1 Pathak et al. 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 extension fee 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 date of this final action. In the interests of compact prosecution, Applicant is invited to contact the examiner via electronic media pursuant to USPTO policy outlined MPEP § 502.03. All electronic communication must be authorized in writing. Applicant may wish to file an Internet Communications Authorization Form PTO/SB/439. Applicant may wish to request an interview using the Interview Practice website: http://www.uspto.gov/patent/laws-and-regulations/interview-practice. Applicant is reminded Internet e-mail may not be used for communication for matters under 35 U.S.C. § 132 or which otherwise require a signature. A reply to an Office action may NOT be communicated by Applicant to the USPTO via Internet e-mail. If such a reply is submitted by Applicant via Internet e-mail, a paper copy will be placed in the appropriate patent application file with an indication that the reply is NOT ENTERED. See MPEP § 502.03(II). Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHERROD KEATON whose telephone number is 571-270-1697. The examiner can normally be reached 9:30am to 5:00pm. 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 MICHELLE BECHTOLD can be reached at 571-431-0762. 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. /SHERROD L KEATON/ Primary Examiner, Art Unit 2148 11-12-2025
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Prosecution Timeline

Sep 16, 2022
Application Filed
Jun 28, 2025
Non-Final Rejection — §101, §103
Nov 03, 2025
Response Filed
Nov 15, 2025
Final Rejection — §101, §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
52%
Grant Probability
88%
With Interview (+36.1%)
4y 6m
Median Time to Grant
Moderate
PTA Risk
Based on 563 resolved cases by this examiner. Grant probability derived from career allow rate.

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