DETAILED ACTION
This is responsive to the amendments filed on 04/03/2026 in which claims 1-4, and 6-14 are presented for examination; Claims 1, 6, 13, and 14 have been amended; claim 5 have been cancelled.
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 .
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 1-4, and 6-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 1:
Step 1: Is the claim to a process, machine, manufacture or composition of matter?” Yes, it’s a method(process).
Step 2a Prong 1 (judicial exception)
Step 2A (1): “Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes.
Claim 1 recites:
“A method performed by a computing device for estimating a heart age, the method comprising: obtaining vital sign data of a user; estimating probability information indicating that the user has a particular disease and a heart age of the user based on the vital sign data of the user by using each of a plurality of artificial neural network models, and generating a final output value based on the estimated probability information and estimated heart ages of the plurality of artificial neural network models, wherein an architecture of the plurality of artificial neural network models includes an architecture of ensembling of the plurality of artificial neural network models, and each of the plurality of artificial neural network models corresponds to an artificial neural network model further trained by transfer learning to estimate a heart age based on a pre-trained artificial neural network model for predicting a heart disease.”
All the limitations above are abstract idea related to organizing human activity with the exception of bold and underlined limitations. Claim language pertains to estimating a heart age from vital sign data, which falls under certain methods of organizing human activity. Any data can be analyzed and probability value can be estimated , if the person has a particular disease.
Step 2A(2): Prong Two: evaluate whether the claim recites additional elements that integrate the exception into a practical application of the exception. NO
The claim does recite additional elements; however they don’t integrate the exception into a practical application of the exception.
Computing device (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 - see MPEP 2106.05(f))
pre-trained artificial neural network model, (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 - see MPEP 2106.05(f))
artificial neural network model (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 - see MPEP 2106.05(f))
transfer learning(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 - see MPEP 2106.05(f))
an architecture of the plurality of artificial neural network models includes an architecture of ensembling (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 - see MPEP 2106.05(f))
Step 2B: evaluate whether the claim recites additional elements that amount to an inventive concept (aka “significantly more”) than the recited judicial exception? NO
As discussed previously with respect to Step 2A Prong Two, the additional element in the claim amounts to no more than mere instructions to apply the exception using a generic computer component.
The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Dependent claims 2-4, and 6-12 further narrows the abstract idea described above and add the additional elements of “supervised learning”, “ground-truth label” , “trained heart disease model”, “interpolation network”, “decay rate”, “transfer learning”, “fine-tuning”
Under step 2A, prong two, the additional elements don’t integrate the exception into a practical application of the exception as merely 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 - see MPEP 2106.05(f).
As discussed previously with respect to Step 2A Prong Two, the additional elements in the claim amounts to no more than mere instructions to apply the exception using a generic computer component.
The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Regarding claim 13, under step 1 the claim does not fall under any statutory category, as claim 13 refers to “a computer program”, which is software per se. For compact prosecution, the examiner will carry out the remaining steps of 35 U.S.C 101 analysis.
Claim 13 is rejected under the same rationale as claim 1, and adds the additional elements of “computer program”, “non-transitory computer-readable storage medium”, “computing device”.
Under step 2A, prong two, the additional elements don’t integrate the exception into a practical application of the exception as merely 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 - see MPEP 2106.05(f).
As discussed previously with respect to Step 2A Prong Two, the additional elements in the claim amounts to no more than mere instructions to apply the exception using a generic computer component.
The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Regarding claim 14, it is rejected under the same rationale as claim 1, and adds the additional elements of “computing device”, “processor”, “network unit”, “memory”.
Under step 2A, prong two, the additional elements don’t integrate the exception into a practical application of the exception as merely 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 - see MPEP 2106.05(f).
As discussed previously with respect to Step 2A Prong Two, the additional elements in the claim amounts to no more than mere instructions to apply the exception using a generic computer component.
The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Allowable Subject Matter
Claims 1-4, and 6-14 are allowable over prior art. Please see office action mailed on 01/07/2026 for further details (Pg. 7-8).
Response to Arguments
Applicant's arguments filed on 04/03/2026 have been fully considered but they are not persuasive.
Remarks - 35 USC § 101
In remarks, Pg. 8, applicant contends: “additionally, following the incorporation of Claim 5, Claim 1 is further limited that the structure of the plurality of artificial neural network models includes an ensembling structure. Thus, the amended Claim 1 discloses a technical configuration that specifically defines the training method and the operational structure of the models, rather than a simple use of Al.”
The inclusion of claim 5 limitations, further clarifies that machine learning being claimed is merely at apply it level, as the applicant is specifically claiming “the structure of the plurality of artificial neural network models includes an ensembling structure.” The claims or the specification don’t provide any details as to what problem in ensemble learning is being solved or what and how the improvement to the ensemble learning is being made; the claim rather merely recite the use of ensemble structure.
In remarks, Pg. 8, applicant contends: “specifically, the core of amended Claim 1 is that heart age estimation is not merely automation of general regression or simple data analysis, but involves transfer-learning a model already trained for disease prediction to fit a different task-heart age estimation-and operating a plurality of such transfer-learned models in an ensemble structure to generate a final output value. This does not merely present an abstract goal of "calculating heart age"; it specifically defines what type of models are used, what pre-trained state they are based on, what additional training process they undergo, and in what structure they operate in combination. In other words, this claim seeks protection for the specific technical means of how to configure, train, and operate Al models, rather than the use of Al itself.”
The claim does detail wat type of models are being used, pre-trained state, additional training etc...; however, these concepts are disclosed in claims and specification at only apply it level. Note, transfer learning, ensemble structure etc... are treated as additional limitation, and examiner acknowledges that these concepts are not merely abstract idea; however, transfer learning and ensemble structures are conventional techniques that are used in machine learning. At this point, we are merely using/applying these known techniques in machine learning to the abstract idea. As mentioned above, the claims or specification don’t add any technical details that show improvement into the machine learning technology, transfer learning, or ensemble structures.
In remarks, Pg. 8, applicant contends: “this configuration is also distinguished from a mere "field of use" limitation. Transfer- learning a pre-trained disease prediction model to fit heart age estimation is a technical improvement that enables more stable and sophisticated heart age estimation from vital sign data by adjusting representations and parameters previously formed for disease classification to fit a new task. Furthermore, the ensemble structure of multiple models is a structural design that reduces dependency on a single model and provides more robust results even for user groups with diverse pathological conditions by synthesizing outputs from multiple models that have learned different disease-related features.”
What applicant is describing above are benefits of transfer learning and ensemble learning; by applying these concepts to heart age estimation, or related data, no technical improvement is being presented in these techniques, rather only different type of data is being used in the models.
In remarks, Pg. 9, applicant contends: “Desjardins clarifies that Desjardins has been designated as precedential and should be applied consistently with existing Federal Circuit precedents regarding improvements in computer functionality or other technological fields. In particular, the memorandum explains that improving the training method of a machine learning model or improving computer performance through the adjustment of parameters related to a machine learning model can be examples of an improvement in computer functionality.”
The current claims don’t provide improved training method of a machine learning model or improved computer performance through the adjustment of parameters related to a machine learning model can be examples of an improvement in computer functionality. The training methods being used are at generic level; in fact the claims literally state using transfer learning, and ensemble structure methods. Furthermore, the claims don’t indicate any improvement to computer performance, unless applicant is referring to improvement due to transfer learning, which is result of using transfer learning rather than applicant’s solution or specific configuration.
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUMA WASEEM whose telephone number is (571)272-1316. The examiner can normally be reached Monday-Friday(9:00am - 5:00 pm) EST.
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/HUMA WASEEM/Examiner, Art Unit 3686
/JASON B DUNHAM/Supervisory Patent Examiner, Art Unit 3686
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