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 .
DETAILED ACTION
Response to Amendment
The present Office Action is in response to the Request for Continued Examination dated 02 March 2026.
In the amendment dated 02 March 2026, the following has occurred: Claims 1, 21, 28, and have been amended.
Claims 1, 3-5, 7, 8, 10-12, and 17-29 are pending, with claims 17-20 being withdrawn. Claims 1, 3-5, 7, 8, 10-12, and 21-29 are examined.
Request for Continued Examination
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 02 March 2026 has been entered.
Priority
This application claims priority to U.S. Provisional Patent Application No. 63/421,364 dated 01 November 2022.
Claim Rejections - 35 USC § 103
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.
The following is a quotation of 35 U.S.C. § 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 3-5, 7, 8, 10-12, and 21-29 is/are rejected under 35 U.S.C. § 103 as being unpatentable over Hayward et al. (U.S. Pre-Grant Patent Publication No. 2023/0260048) in view of Che et al. (U.S. Pre-Grant Patent Publication No. 2025/0131184).
REGARDING CLAIM 1
Hayward teaches the claimed system for predicting a payment amount to settle a medical claim comprising:
a deep neural network including an input layer, an output layer, and a plurality of interior layers connecting the input layer to the output layer, […]; [Para. 0061, 0116 teaches an ANN having nodes arranged in multiple layers. Para. 0124 teaches that the ANN is a deep learning neural network; a deep learning neural network includes an input, output and connecting interior layers by definition.]
a computing device including a processor and a memory in network communication with at least one database, [Abstract, Fig. 2, Para. 0088, 0090, 0095, 0124 teaches a server (computer) having a processor, memory, artificial neural network (ANN), and a database. Para. 0124 teaches that the ANN is a deep learning neural network. A deep learning neural network includes an input, output and connecting interior layers by definition. See Fig. 3.] the computer network configured to train the deep neural network, [Para. 0052 teaches an AI platform. Para. 0156 teaches that the AI platform is on a computer.]
wherein training the deep neural network further comprises:
collecting a plurality of associated with a medical claim; [Para. 0051 teaches that data associated with a claim is retrieved.]
inputting the plurality of collected data to the deep neural network:
outputting, based on the plurality of collected data, […first data…]; [Para. 0055 teaches that the neural network outputs a settlement offer (first data).]
retraining the deep neural network using the […first data…]; [Para. 0114 teaches that the model (the neural network) is updated dynamically (interpreted as retraining) to take into account newly-settled claims (interpreted to settlement offers, i.e., first information).]
collecting, […second data…], […third data…], and […fourth data…]; and [Para. 0063 teaches that historical data is retrieved. Para. 0070 teaches that historical data includes notes (interpreted as second data), photographs (interpreted as third data), and written records (interpreted as fourth data).]
retraining the deep neural network using the […second, third, and fourth data…]. [Para. 0114 teaches that the model (the neural network) is updated dynamically (interpreted as retraining) to take into account newly-settled claims (interpreted to include historical information about the claim including second, third, and fourth information). See also, Para. 0131.]
Hayward may not explicitly teach data in the form of
a first offer including a payment amount
data associated with a denial by a medical provider of the first offer
data associated with an appeal of the denial
provider geographic data
However, the limitation claims information/labels that constitute nonfunctional descriptive information that is/are not functionally involved in the recited system. The function described by the system would be performed the same regardless of whether the claimed information/labels was substituted with nothing. Because Hayward teaches a collecting claims-related data and training and retraining a DNN using various related data, substituting the information/labels of the claimed invention for the information/labels of the prior art would be an obvious substitution of one known element for another, producing predictable results. Therefore, would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have substituted the information/labels applied to the received patient data of the prior art with any other information/labels because the results would have been predictable. MPEP 2112.01, Section III (see also In re Ngai, Ex Parte Breslow). The Examiner notes that there is no indication how the claim-related data would affect the outcome of the claim and thus the type of data is nonfunctional.
Hayward may not explicitly teach
wherein the deep neural network includes a long short-term memory (LSTM) network;
The Examiner notes that the claim merely states that the DNN “includes” and LSTM, with no indication as to whether the LSTM is actually used to perform a function in the claim. As such, this too could be considered non-functional descriptive information; however, for completeness, Chen has been cited to explicitly teach this feature. The Examiner suggests positively reciting that the LSTM is used in the claim.
Chen at Item 452, Fig. 4, Para. 0082-0084 teaches that it was known in the art of computerized healthcare, at the time of filing, to utilize an LSTM network as part of a deep neural network to analyze medical information
wherein the deep neural network includes a long short-term memory (LSTM) network; [Chen at Item 452, Fig. 4, Para. 0082-0084 teaches utilizing a DNN that uses LSTM models to generate output data from analyzed information (the information of Heyward).]
Therefore, it would have been prima facie obvious to one of ordinary skill in the art of computerized healthcare, at the time of filing, to modify the DNN training system of Hayward to utilize an LSTM network as part of a deep neural network to analyze medical information as taught by Chen, with the motivation of improving the accuracy of information analysis (see Chen at Para. 0003).
REGARDING CLAIMS 3-5, 7, 8, AND 10-12
Hayward/Chen teaches the claimed system for training a neural network configured for determining an action item associated with a group health care plan of Claim 1. Hayward may not explicitly teach
Claim 3: wherein the medical claim is a bill for medical and/or healthcare services.
Claim 4: wherein the data associated with the medical claim includes an identity of a provider of medical and/or healthcare services associated with the medical claim.
Claim 5: wherein the data associated with the medical claim includes an identity of a patient of medical and/or healthcare services associated with the medical claim.
Claim 7: wherein the data associated with the medical claim includes a value of an accepted offer to settle the medical claim.
Claim 8: wherein the data associated with the medical claim includes a rate of claims accepted for adjudication.
Claim 10: wherein the data associated with the medical claim includes an outcome of the appeal.
Claim 11: wherein the data associated with the medical claim includes genetic information of a patient of medical and/or healthcare services associated with the medical claim.
Claim 12: wherein the data associated with the medical claim includes an outcome of a patient following a medical and/or healthcare service associated with the medical claim.
However, these limitations claim information/labels that constitute nonfunctional descriptive information that is/are not functionally involved in the recited system. The function described by the system would be performed the same regardless of whether the claimed information/labels was substituted with nothing. Because Hayward teaches a collecting claims-related data and training and retraining a DNN using various related data, substituting the information/labels of the claimed invention for the information/labels of the prior art would be an obvious substitution of one known element for another, producing predictable results. Therefore, would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have substituted the information/labels applied to the data inputted into the DNN of the prior art with any other information/labels because the results would have been predictable. MPEP 2112.01, Section III (see also In re Ngai, Ex Parte Breslow). The Examiner notes that there is no indication how the inputted data would affect the outcome of the claim and thus the type of data is nonfunctional.
REGARDING CLAIM(S) 21
Claim(s) 21 is/are analogous to Claim(s) 1, thus Claim(s) 21 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 1.
REGARDING CLAIM(S) 22-29
Claim(s) 22-29 is/are analogous to Claim(s) 3-5, 7, 8, and 10-12, respectively, thus Claim(s) 22-29 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 3-5, 7, 8, and 10-12.
Response to Arguments
Claim Objections
Regarding the objections to Claim 1, the Applicant has amended the claim to overcome the bases of objection.
Rejection under 35 U.S.C. § 103
Regarding the rejection of Claims 1, 3-5, 7, 8, 10-12, and 21-29, the Examiner has considered Applicant’s arguments; however, these arguments are moot given the new grounds of rejection as afforded by the present RCE.
Conclusion
Prior art made of record though not relied upon in the present basis of rejection are noted in the attached PTO 892 and include:
Brown et al. (U.S. Pre-Grant Patent Publication No. 2024/0127912) which analyzing information to identify an event and then prompts for supporting information.
Krogan et al. (U.S. Pre-Grant Patent Publication No. 2023/0395193) which discloses a system that predicts responsiveness of a subject to a drug.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JASON S TIEDEMAN whose telephone number is (571)272-4594. The examiner can normally be reached 7:00am-4:00pm, off alternate Fridays.
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, Robert Morgan can be reached at 571-272-6773. 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.
/JASON S TIEDEMAN/Primary Examiner, Art Unit 3683
Prosecution Insights