Notice of Pre-AIA or AIA Status
The present application is being examined under the pre-AIA first to invent provisions.
DETAILED ACTION
Status of the Application
Claims 1-20 are currently pending in this case and have been examined and addressed below. This communication is a Final Rejection in response to the Amendment to the Claims and Remarks filed on 10/17/2025.
Claim 7 is currently amended
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 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1-7 fall within the statutory category of a process. Claims 8-14 fall within the statutory category of an article of manufacture as a computer-readable medium. Claims 15-20 fall within the statutory category of an apparatus or system.
Step 2A, Prong One
As per Claims 1, 8, and 15, the limitations of diagnosing a patient which includes receiving a patient identification of a patient, receiving geographic location of a computer system, receiving patient’s chief complaint and interview data, receiving current body characteristics of the patient, creating a multimedia representation for each body characteristic, identifying previous multimedia representations of each body characteristic from other persons, comparing the current to previous multimedia representations, identifying potential matches with corresponding confidence factors in accordance with defined medical standards, using diagnostic templates for a set of known illnesses, maladies, diseases, infections, conditions or traumas along with their associated data, signs and symptoms based in part on geographic location and the patient’s chief complaint to select a diagnosis and diagnosis confidence factor for the patient based on comparing the current and previous multimedia representations; determining that the diagnosis is of highest probability of being the correct diagnosis in accordance with defined medical standards and in response to the diagnosis confidence factor of the diagnosis exceeding a confidence factor threshold; in response to the diagnosis confidence factor not exceeding the confidence factor threshold, selecting a different current body characteristic of the patient to determine to increase the diagnosis confidence factor, wherein selection of the different body characteristic is based on the one or more current body characteristics of the patient previously determined and based on an order of selection in order to exceed the high confidence factor threshold with a minimum number of additional selections of different body characteristics; and in response to the diagnosis confidence factor exceeding the confidence factor threshold, selecting the diagnosis as the diagnosis for the patient; and selecting a treatment based on the diagnosis, under its broadest reasonable interpretation, covers managing interactions between people and personal behaviors. The steps of diagnosing a patient, determining the diagnosis is of highest probability of being the correct diagnosis, selecting a different body characteristic to increase the confidence factor, selecting the diagnosis, and selecting a treatment are concepts performed by a physician in the treatment and diagnosis of a patient which is an interaction between patient and physician in routine patient care. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or interactions between people, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application because the additional elements and combination of additional elements do not impose meaningful limits on the judicial exception. In particular, the claims recite the additional elements – a non-transitory machine-readable storage media comprising instructions (Claim 8), a processor (Claim 8, 15) to execute the instructions. The computer-readable media and processor in these steps is recited at a high-level of generality, such that it amounts to 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. The claims recite sensors which generate current body characteristics, where the sensors are recited at a high-level of generality and therefore amount to mere instructions to apply the exception as they are general purpose computer components used in their ordinary capacity to measure values, as per MPEP 2106.05(f)(2). The claims recite the use of trained classifiers, trained diagnostic engines of the computer system, and trained arbitrators to execute steps of the abstract idea including identifying multimedia representations of body characteristics of other persons, selecting a diagnosis and diagnosis confidence factor for the patient, and determining a diagnosis with the highest probability. The trained classifiers are described as decisions trees or other machine learning models (specification [0059]) and the trained diagnostic engine is described as expert system, state machine, classifier, etc. (specification [0059]). The trained arbitrators are not specifically described. These are known mathematical algorithms, and as per MPEP 2106.05(f)(2), use of a commonplace mathematical algorithm applied on a general purpose computer merely invokes computers or machinery as a tool to perform the process and therefore amounts to mere instructions to apply the exception. The claims also recite the additional elements of receiving electronic data, which amounts to insignificant extra-solution activity, as in MPEP 2106.05(g), because the steps of receiving electronic data are mere data gathering in conjunction with the abstract idea where the limitation amounts to necessary data gathering and outputting, (i.e., all uses of the recited judicial exception require such data gathering or data output). See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering). Because the additional elements do not impose meaningful limitations on the judicial exception, the claim is directed to an abstract idea.
Step 2B
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 discussed above with the respect to integration of the abstract idea into a practical application, the additional element of a processor and non-transitory machine-readable storage media comprising instructions to perform the method of the invention amounts to no more than mere instructions to apply the exception using a generic computing component. The processor is recited at a high level of generality as generic computer components by reciting any suitable processor architecture (Specification, [0062]). The machine-readable media is described as any mechanism which provides information in a form accessible by a machine (Specification [0105]). These do not add meaningful limitations to the abstract idea beyond mere instructions to apply an exception. The use of trained classifiers, trained diagnostic engines, and trained arbitrators are found to be mere instructions to apply the exception, as above. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims also include the additional elements of receiving electronic data which is well-understood, routine and conventional computer functions in the field of data management because they are claimed at a high level of generality and include receiving or transmitting data, which have been found to be well-understood, routine and conventional computer functions by the Court (MPEP 2106.05(d)(II)(i) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of the computer or improves another technology. The claims do not amount to significantly more than the underlying abstract idea.
Dependent Claims 2-7, 9-14, and 16-20 add further limitations which are also directed to an abstract idea. For example, Claims 2, 9, and 16 include using trained classifiers, which similar to the independent claims is an additional element which amounts to mere instructions to apply the exception as mathematical calculations to apply the abstract idea. The algorithms are recited at a high level of generality for the purpose of optimizing recognition of data sources, which is the result of invoking computers to perform the abstract idea. As per MPEP 2106.05(f), claiming the improved speed or efficiency inherent with applying the abstract idea on a computer does not integrate the abstract idea into a practical application or provide significantly more.
Claims 3-4, 10-11, and 17-18 further specify or limit the elements of the independent claims, and hence are nonetheless directed towards fundamentally the same abstract idea as independent Claims 1, 8, and 15.
Claims 5, 12, and 19 recite downloading remote patient data from a local and remote server which is an additional element which amounts to mere data gathering that is insignificant extra-solution activity.
Claims 6, 13, and 20 recite retrieving historical data of the patient which is also mere data gathering. The data gathering steps, similar to the independent claims are well-understood, routine and conventional because receiving or transmitting data over a network and storing and retrieving information in memory are computer functions found to be well-understood, routine and conventional by the courts, as per MPEP 2106.05(d)(II).
Claim 7 recites using computerized trained diagnostic engines of a machine-learning model with diagnostic templates. The use of trained diagnostic engines of a machine-learning model to execute steps of the abstract idea amounts to mere instructions to apply the exception. The trained classifiers are described as decisions trees or other machine learning models (specification [0059]) and the trained diagnostic engine is described as expert system, state machine, classifier, etc. (specification [0059]). The specification describes the diagnostic templates as machine learning models ([0033]). These are known mathematical algorithms, and as per MPEP 2106.05(f)(2), use of a commonplace mathematical algorithm applied on a general purpose computer merely invokes computers or machinery as a tool to perform the process and therefore amounts to mere instructions to apply the exception.
Claim 14 recites determining an illness of the patient corresponds to known side effects of current medications of the patient which is directed to organizing human activity because it is part of the process of a physician diagnosing a patient and is the same reasons as the independent claims. Because the additional elements do not impose meaningful limitations on the judicial exception and the additional elements are well-understood, routine and conventional functionalities in the art, the claims are directed to an abstract idea and are not patent eligible.
Subject Matter Free of the Prior Art
The combination of elements of Claims 1, 8, and 15 are free of the prior art. Specifically, using trained diagnostic engines with diagnostic templates for a set of known illnesses, maladies, diseases, infection, conditions or traumas along with their associated data, signs, and symptoms based in part upon geographic location and the patient’s chief complaint to select a diagnosis and a diagnosis confidence factor for the patient based on comparing the current multimedia representation to a previous number of multimedia representations derived from previous patients of each of one or more body characteristics in accordance with defined medical standards in combination with the receiving of all of the recited data including patient identification, geographic location of the computer system, chief complaint and interview data, and current body characteristics is free of the prior art from before the filing date of the present application.
Response to Arguments
Applicant’s arguments, see Pages 12-15, “§101 Rejection of the Claims”, filed 10/17/2025 with respect to claims 1-20 have been fully considered but they are not persuasive.
Applicant argues that the claims of the present application are not directed to an abstract idea because they do not recite mental steps or data processing, but rather are directed to a specific computer-implemented diagnostic methodology. Applicant further argues that the claims include hardware-based data acquisition, multimedia pattern recognition, machine learning-based diagnostic engines, and an arbitrator engine which are the computer-implemented diagnostic methodology that is a machine-controlled procedure and not a human activity of diagnosis. Examiner respectfully disagrees. The computer components and functionality which is recited in the claims is used to execute the abstract idea itself. The claims are directed to a method of determining a diagnosis for a patient and selecting a treatment based on the diagnosis which includes all of the steps of the claims recited in the rejection above, which is activity that is routinely performed by a physician during a healthcare interaction with a patient. This falls into the abstract grouping of certain methods of organizing human activity. The use of a non-transitory machine-readable storage media comprising instructions and a processor amounts to mere instructions to apply the exception because these are general purpose computer components being used to execute the abstract idea. The claims recite sensors which generate current body characteristics, where the sensors are recited at a high-level of generality and therefore amount to mere instructions to apply the exception as they are general purpose computer components used in their ordinary capacity to measure values, as per MPEP 2106.05(f)(2). The trained classifiers, machine learning based diagnostic engines, and trained diagnostic engines are described in the specification as types of mathematical algorithms, as described in the rejection above. The use of mathematical algorithms to carry out steps of the abstract idea amounts to mere instructions to apply the exception, which does not provide a technical improvement. The use of computers or other machinery to perform the abstract idea, as per MPEP 2106.05(f)(2), does not integrate the abstract idea into a practical application or provide significantly more. The claims do not need to recite that the steps are performed by the human to fall into the abstract grouping of certain methods of organizing human activity. The functionality which is performed by the computer components in the claims is activity which is performed by humans, but is applied to computer components or machinery and therefore it falls into the abstract idea of certain methods of organizing human activity.
Applicant argues that the claims integrate the abstract idea into a practical application. Applicant further argues that the use of trained machine learning models; execution within a defined computing environment including a processor, memory, diagnostic engines, and trained arbitrator; application of high confidence factor thresholds; and generation of tangible treatment outputs provide specific technological implementation which provides improvement to the accuracy and efficiency of the diagnostics provides a practical application. Examiner respectfully disagrees. The application of medical defined high confidence factor thresholds is recited in the claims as determining the diagnosis is of the highest probability of being the correct diagnosis in response to the diagnosis confidence factor exceeding a confidence factor threshold. This is part of the abstract idea itself and therefore cannot integrate the abstract idea into a practical application. Similarly, generation of tangible treatment outputs is also part of the abstract idea itself and cannot integrate the abstract idea into a practical application. The improvements are to the abstract idea itself. No matter how much of an advance in the determination of a diagnosis and selecting a treatment the claims recite, the advance lies entirely in the realm of abstract ideas, with no plausibly alleged innovation in the nonabstract application realm. An advance of that nature is ineligible for patenting. The use of trained machine learning models amounts to mere instructions to apply the exception because applying mathematical algorithms to execute the steps of the abstract idea has been found by the courts to be mere instructions to apply the exception, as per MPEP 2106.05(f)(2). The use of a defined computing environment including a processor, memory, diagnostic engines, and trained arbitrator also amounts to mere instructions to apply the exception because the use of general purpose computing components to execute the abstract idea is mere instructions to apply the exception, as per MPEP 2106.05(f)(2). As per the rejection above, these elements are recited at a high-level of generality such that they are general purpose computing components and/or mathematical algorithms. Therefore, the claims do not integrate the abstract idea into a practical application and the rejection is maintained.
Applicant argues that the claims recite a machine-implemented improvement as improving diagnostic certainty using multi-layer trained AI components structured per medical standards because this is similar to claims that the Appeals Review Panel decision made regarding claims directed to training machine learning models. Examiner notes that examination of 101 subject matter eligibility follows the process laid out in the MPEP and does not consider particular non-precedential cases. However, the claims in the present application do not recite training machine learning models. The claims merely recite the use of an already trained classifier and diagnostic engine. This does not provide technical improvement but merely includes the application of already developed mathematical algorithms.
Applicant argues that the claims provide significantly more than the abstract idea because the ordered combination of features including real-time sensor data, multi-media comparison via machine learning, and high-confidence threshold arbitration improves computer performance itself. Examiner respectfully disagrees. The reduction in testing which results from the improved diagnostic abilities are a result of the abstract idea itself and the improved process of decision making. This is not an improvement to the computer or technology. The use of machine learning which results in a better or more accurate calculation which is used to determine a diagnosis and treatment amounts to mere instructions to apply the exception, which does not amount to significantly more than the abstract idea. There is no evidence that the computer itself is improved in any way, only an improvement to the diagnosis and treatment provided for a patient.
Conclusion
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 Evangeline Barr whose telephone number is (571)272-0369. The examiner can normally be reached Monday to Friday 8:00 am to 4:00 pm.
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/EVANGELINE BARR/Primary Examiner, Art Unit 3682