DETAILED ACTION This Office Action is in response to the application 1 8 / 223 , 597 filed on July 19 th , 202 3 . 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 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. Claims 1- 15 are pending and herein considered. 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. Priority Acknowledgement is made of Applicant’s claim for foreign priority under 35 U.S.C. 119(a)-(d) to Application No. 202221041590 , the signed copy having been filed on July 20 th , 202 2 . 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. C laims 1- 15 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. Regarding claims 1 and 11 ; claims 1 and 11 are/is rejected under 35 USC 101 because the claims are/is directed to an abstract idea without being integrated into a practical application nor being significantly more. The claims reciting the limitations “ build [ ing ] an initial behavior knowledge model associated with one or more behaviors of a subject to be monitored ,” “ simulat [ ing ] the initial behavior knowledge model, with a set of randomized occurrence patterns of events that produce the one or more behaviors, to obtain a time-series training data ,” “ transform [ ing ] the time-series training data to obtain a feature engineered training data , ” “ train [ ing ] a machine learning (ML) model with the feature engineered training data to obtain a trained ML model for the one or more behaviors , ” “ apply [ ing ] the trained ML model on a real-world data to predict an outcome data relevant to the one or more behaviors, ” “ determin [ ing ] one or more deviations in the initial behavior knowledge model by comparing the time-series training data, the real-world data, and the outcome data ” and “ fine-tun [ ing ] the initial behavior knowledge model with the one or more deviations is performed until the time-series training data arising out of the behavior knowledge model is close to the real-world data ” are directed to an abstract idea as the claims recite mental processes. Accordingly, the claims recite an abstract idea. This judicial exception is not integrated into a practical application. It’s noted that the claims recite additional element(s) ( i.e , one or more hardware processors ) . However, said additional element is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of building/simulating/transforming/training/applying/determining/fine-tuning ) such that it amounts no more than mere instructions to apply the exception using a generic computer component. 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. Therefore, the claims are not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. As mentioned above, although the claims recite additional element, said element taken individually or as a combination, do not result in the claim amounting to significantly more than the abstract idea because as the additional elements perform generic computer content distributing functions routinely used in information technology field. F ine-tuning the initial behavior knowledge model with the one or more deviations is performed until the time-series training data arising out of the behavior knowledge model is close to the real-world data is conventional, well know routing in view of Berkeeimer memo here. Generic computer components recited as performing generic computer functions that are well understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. Therefore, the claim is directed to non-statutory subject matter. Regarding claims 2-10 & 12-1 5 ; claims 2-10 & 12-1 5 are also rejected under 35 U.S.C 101 as being directed to non-statutory subject matter for the same reasons addressed above as the claims are directed to abstract idea without being integrated into a practical application nor being significantly more. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to FILLIN "Examiner name" \* MERGEFORMAT KHOI V LE whose telephone number is FILLIN "Phone number" \* MERGEFORMAT (571)270-5087 . The examiner can normally be reached FILLIN "Work Schedule?" \* MERGEFORMAT 9:00 AM - 5:00 PM EST . 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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. /KHOI V LE/ Primary Examiner, Art Unit 2436