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 .
1. In response to the Office Action dated on 02/05/2026, applicant(s) amend the application as follow:
Claims amended: 1, 9 and 15
Claims canceled:2-8, 10-14 and 16-20
Claims newly added:
Claims pending: 1, 9, 15 and 21-37
Response to Arguments
2. Applicant’s arguments with respect to claim(s) 1, 9 and 15 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
In the interview on 12/03/2026, examiner initially agreed with applicant proposed amendment has overcome the 101 rejection. After checking, the claims amendment has not overcome the 101 rejection. Examiner apologized for earlier comment.
Applicant argues “… For these reason, proposed claim is patent-eligible under 35 U.S.C 101 and the claim rejection under that section should therefore be withdrawn.”
Examiner respectfully disagrees with the above argument. The claims include mental steps including identifying and generating. These other additional elements which generalization concepts. The additional elements do not amount to significantly more.
Applicant argues “Bellega et al. does not cure the short coming of Shah with respect to amended claims…”
Please see the new cited references.
Information Disclosure Statement
3. The information disclosure statement (IDS) submitted on 01/08/2026. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
4. Claims 1, 9, 15 and 21-37 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 9, 15 and 21-37 of copending Application No. 19/989,921(reference application). Although the claims at issue are not identical, they are not patentably distinct from each other because both applications language direct to similar subject matter including obtaining a transcript of a conversation between a healthcare provider and a patient, the transcript including unstructured patient information, segmenting, by a large language model (LLM), the transcript into segments based on the unstructured patient information, Identifying, for each of the segments, one or more examples of structured information formats, in an examples database, that are relevant to the particular instance of unstructured patient information included in the corresponding segment, wherein the examples database provides a full set of examples of structured information formats for populating an electronic health record (EHR) flowsheet, generating input prompts based on the segments, wherein each of the input prompts includes a corresponding one of the segments and the one or more examples of structured information formats that are relevant to the particular instance of unstructured patient information included in the corresponding segment, processing the input prompts using a generative artificial intelligence (AI) model to extract structured patient information for populating the EHR flowsheet and populating the EHR flowsheet using the structured patient information” is the process for storing information into the database for later retrieval. The differences are, the instant application include identifying one or more example flowsheet, while the 921 includes identifying one or more rows of an electronic health records (HER). Therefore, it would have been obvious to one ordinary skill in the art to modify 921 to include example to arrive the same invention.
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
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.
5. Claims 1, 9, 15 and 21-37 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more.
Step 1 (See MPEP 2106)
Claims 1, 9, 15 and 21-37 are directed to a method, a system and a tangible , non-transitory computer readable medium which belongs to a statutory class.
Step 2A, Prong One:
Claims recites limitation
“Identifying, for each of the segments, one or more examples of structured information formats, in an examples database, that are relevant to the particular instance of unstructured patient information included in the corresponding segment, wherein the examples database provides a full set of examples of structured information formats for populating an electronic health record (EHR) flowsheet”
“Generating input prompts based on the segments, wherein each of the input prompts includes a corresponding one of the segments and the one or more examples of structured information formats that are relevant to the particular instance of unstructured patient information included in the corresponding segment”
The identifying and generating” are processes that, under its broadest reasonable interpretation, covers performance of the limitation by Mental Process, but for the recitation of generic computer components. Nothing in the claim element precludes the steps from practically being performed in the human mind. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation by mental process, but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A, Prong Two:
Claims recites computer processor and instructions which are computer component and logic to perform the computer operation. These are generic computer components and program which use to perform abstract ideas.
“Obtaining a transcript of a conversation between a healthcare provider and a patient, the transcript including unstructured patient information; including a plurality of portions” is the processing of receiving the information for analysis or retrieval.
“Segmenting, by a large language model (LLM), the transcript into segments based on the unstructured patient information, wherein each of the segments includes a particular instance of the unstructured patient information.” is the process of dividing information to sections for processing.
‘’Processing the input prompts using a generative artificial intelligence (AI) model to extract structured patient information for populating the EHR flowsheet (the input prompt also instruction on how to format the output, for example into a JSON format) (paragraph 0103); and
“Populating the EHR flowsheet using the structured patient information” is the process for storing information into the database for later retrieval.
The limitation is thus insignificant extra-solution activity. Limitations that the courts have found not to be enough to qualify as "significantly more” when recited in a claim with a judicial exception include: i. Adding the words "apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 134 S. Ct. at 2360, 110 USPQ2d at 1984 (see MPEP § 2106.05(f)). 2106.05(g)--Insignificant Extra-Solution Activity.
At Step 2B:
The conclusions for the mere implementation using a computer are carried over and does not provide significantly more.
Looking at the claim as a whole does not change this conclusion and the claim is ineligible.
As to claims 21 and 29-30, the limitation “the LLM is configured to keep related pieces of the unstructured patient information together is a corresponding one of the segments”
As to claims 22 and 31, the limitation “the one or more examples of structured information formats include at least one example of structured information for a key-value pair in the EHR flowsheet” is only further defined what the one or more examples of the structure information format is and insignificant to amount significantly more.
As to claims 23 and 32, the limitation “at least some of the segments overlap with each other” is only further defined what some of the segments are and insignificantly to amount significantly more.
As to claim 24, the limitation “wherein the one or more examples of structured information formats include at least one example of structured information for a particular row of the EHR flowsheet” is only further defined what the one or more examples of structured information formats are and insignificantly to amount significantly more.
As to claims 25 and 34, the limitation “LLM is separate and distinct from the generative AI mode” is only further defined what LLM and generative AI model are and insignificantly to amount significantly more.
As to claims 26 and 35, the limitation “the input prompts are generated by a retrieval augmented generation (RAG) model” is only further defined on how the input prompt was generated and significantly to amount significantly more.
As to claims 27 and 36, the limitation “the RAG model identifies which rows of the EHR flowsheet are relevant to the particular instances of unstructured patient information in the corresponding segments prior to generating the input prompts” is only further defined what RAG model function is and insignificantly to amount significantly more.
As o claims 28 and 37, the limitation “the RAG model forwards the input prompts to the generative AI model” is further what the RAG model function is and insignificantly to amount significantly more.
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 (i.e., changing from AIA to pre-AIA ) 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, 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
6. Claim(s) 1, 9, 15 and 21-37 is/are rejected under 35 U.S.C. 103 as being unpatentable over Weston et al. (Pub. No. US 2025/0132036 A1) in view of Gelgi et al. (Pub. No. US 2025/0156567 A1).
As to claim 1. (Currently Amended) Weston discloses a computer implemented method, executed on a computing device, comprising:
processing obtaining a transcript of a conversation between a healthcare provider and a patient, the transcript including unstructured patient information; including a plurality of portions (transcript) (paragraph 0115);
segmenting, by a large language model (LLM) (ML model) (paragraph 0115), the transcript into segments based on the unstructured patient information, wherein each of the segments includes a particular instance of the unstructured patient information (segment transcript into component) (paragraph 0115);
processing the input prompts using a generative artificial intelligence (AI) model to extract structured patient information for populating the EHR flowsheet (the input prompt also instruction on how to format the output, for example into a JSON format) (paragraph 0103); and
populating the EHR flowsheet using the structured patient information (the template may be an structured text or, less preferably, an image file, which can be encoded into a structured format by an encoder template in the template data 112 can include schema for worksheets to be filled in by a clinician or in addition) (paragraph 0075).
Weston discloses identifying, for each of the segments, one or more examples of structured information formats, in an examples database, that are relevant to the particular instance of unstructured patient information included in the corresponding segment, wherein the examples database provides a full set of examples of structured information formats for populating an electronic health record (EHR) flowsheet and generating input prompts based on the segments, wherein each of the input prompts includes a corresponding one of the segments and the one or more examples of structured information formats that are relevant to the particular instance of unstructured patient information included in the corresponding segment.
Gelgi discloses identifying, for each of the segments, one or more examples of structured information formats, in an examples database, that are relevant to the particular instance of unstructured patient information included in the corresponding segment, wherein the examples database provides a full set of examples of structured information formats for populating an electronic health record (EHR) flowsheet the prompts which are to be included with the text description as inputs to the LLM classifier which are to be included with the text description as inputs to the LLM classifier are then generated step S508) (paragraph 0080)
and generating input prompts based on the segments, wherein each of the input prompts includes a corresponding one of the segments and the one or more examples of structured information formats that are relevant to the particular instance of unstructured patient information included in the corresponding segment (0080 the prompt may be include examples from the security database obtained using RCA as described) (paragraph). Therefore, it would have been obvious to one ordinary skill in the art before the effective filing date of the instant application to modify teaching of Neston to include identifying, for each of the segments, one or more examples of structured information formats, in an examples database, that are relevant to the particular instance of unstructured patient information included in the corresponding segment, wherein the examples database provides a full set of examples of structured information formats for populating an electronic health record (EHR) flowsheet and generating input prompts based on the segments, wherein each of the input prompts includes a corresponding one of the segments and the one or more examples of structured information formats that are relevant to the particular instance of unstructured patient information included in the corresponding segment as disclosed by Gelgi in order to provide storing information for later retrieval.
As to claim 30. (New) Neston discloses the method of claim 1, wherein the LLM is configured to keep related pieces of the unstructured patient information together in a corresponding one of the segments (LLM classification keeps information together) (paragraph 0049).
As to claim 31. (New) Neston discloses the method of claim 1, wherein the one or more examples of structured information formats include at least one example of structured information for a key-value pair in the EHR flowsheet (the input prompt also instruction on how to format the output, for example into a JSON format) (paragraph 0103).
As to claim 32. (New) Gelgi disclose the method of claim 31, wherein the key-value pair in the EHR flowsheet corresponds to a particular row of the EHR flowsheet (database include rows with keys) (paragraphs 0046-0047).
As to claim 33. (New) Gelgi discloses the method of claim 1, wherein at least some of the segments overlap with each other (speech segments within the video…) (paragraph 0013) (paragraph 0013).
As to claim 34. (New) Gelgi discloses the method of claim 1, wherein the LLM is separate and distinct from the generative AI mode (first and second generative models) (paragraph 0006).
As to claim 35. (New) Gelgi discloses the method of claim 1, wherein the input prompts are generated by a retrieval augmented generation (RAG) model (the prompts may be selected using any suitable method such as retrieval argument generation (RAG)…) (paragraph 0055).
As to claim 36. (New) Gelgi discloses the method of claim 35, wherein the RAG model identifies which rows of the EHR flowsheet are relevant to the particular instances of unstructured patient information in the corresponding segments prior to generating the input prompts (AI model identify the information from transcript and used as prompts to the fist generative machine learning) (paragraph 0005).
As to claim 37. (New) Gelgi discloses the method of claim 35, wherein the RAG model forwards the input prompts to the generative AI model (prompts may also be selected form examples in the description database (which may include the training data used to train model used by the description module as well as more up-to-today data…) (the RAG selection model and pass to train model (AI model)) (paragraph 0055).
2. - 8. (Canceled)
Claim 9 is rejected under the same reason as to claim 1, Weston discloses a computing system comprising: one or more processors (controller 102) (paragraph 0070); and memory (memory 104) (paragraph 0070) storing programming instructions (instruction 106) (paragraph 0070) for execution by the one or more processors (controller 102) (paragraph 0070), the programming instructions(instruction 106) (paragraph 0070), upon execution by the one or more processors (controller 102) (paragraph 0070), causing the system to perform the following operations.
Claim 29 is rejected under the same reason as to claim 21.
10. - 14. (Canceled)
Claim 15 is rejected under the same reason as to claim 1, Weston discloses a computer program product residing on a non-transitory computer readable medium (memory 104) (paragraph 0070) storing programming instructions (instruction 106) (paragraph 0070) for execution by one or more processors of a system, the programming instructions, upon execution by the one or more processors (controller 102) (paragraph 0070), causing the system to perform the following operations.
16. - 20. (Canceled)
Claim 21 is rejected under the same reason as to claim 30..
Claim 22 is rejected under the same reason as to claim 31.
Claim 23 is rejected under the same reason as to claim 32.
As to claim 24, Gelgi discloses the computer program product of claim 22, wherein the one or more examples of structured information formats include at least one example of structured information for a particular row of the EHR flowsheet (the selected example from each training dataset may used as a prompt by using retrieval argument (RAG) (Paragraph 0008).
Claim 25 is rejected under the same reason as to claim 34.
Claim 26 is rejected under the same reason as to claim 35.
Claim 27 is rejected under the same reason as to claim 36.
Claim 28 is rejected under the same reason as to claim 37.
Conclusion
7. 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 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.
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BAOQUOC N. TO
Examiner
Art Unit 2154
/BAOQUOC N TO/Primary Examiner, Art Unit 2154
Prosecution Insights