DETAILED ACTION
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 .
Status of Claims
In the response filed November 25, 2025, Applicant amended claims 1-4, 9-12, and 17-20. Claims 1-24 are pending in the current application.
Response to Arguments
Applicant’s arguments with respect to the provisional double patenting rejection have been fully considered and are persuasive. Examiner thanks Applicant for amending the claims. The rejection has been withdrawn.
Applicant's arguments with respect to the rejection under 35 U.S.C. 101 have been fully considered but they are not persuasive. Applicant asserts that claims 1, 9, and 17 include additional elements that improve upon the traditional techniques for automatically generating notes or portions form an audio recording. Examiner respectfully disagrees. In order to evaluate improvements to a technology, the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. If the specification sets forth an improvement in technology, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement. Applicant cites specification paragraphs [0032] and [0033] to show improvements upon traditional techniques. The analysis will include the technological improvements of traditional means being prone to errors and instability due to quality of information begin collected from the patient and poor at recognizing medical information, and overcoming technical problems of input window token limits. Lack of low-cost training, costly licensing and operation, lack of healthcare privacy safeguards pertain to business problems not technical problems resolved by technical improvements. The technical improvements as cited by Applicant are conclusory. The detail needed to show how errors and instability are reduced or how quality of information being collected/recognized is improved are not disclosed in the specification. Therefore, the claims do not improve the technology. The rejection is maintained.
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 1-24 are rejected under 35 U.S.C. 101 because the claims are not directed to patent eligible subject matter.
Claims 1-24 do fall within at least one of the four categories of patent eligible subject matter because the claims recite a machine (i.e., non-transitory computer-readable media and system) and process (i.e., a method).
Although claims 1-24 fall under at least one of the four statutory categories, it should be determined whether the claim wholly embraces a judicially recognized exception, which includes laws of nature, physical phenomena, and abstract ideas, or is it a particular practical application of a judicial exception (See MPEP 2106 I and II).
Claims 1-24 are directed to a judicial exception (i.e., a law of nature, natural phenomenon, or abstract idea) without significantly more.
Part I: Step 2A, Prong One: Identify the Abstract Idea
Under step 2A, Prong One of the Alice framework, the claims are analyzed to determine if the claims are directed to a judicial exception. MPEP §2106.04(a). The determination consists of a) identifying the specific limitations in the claim that recite an abstract idea; and b) determining whether the identified limitations fall within at least one of the three subject matter groupings of abstract ideas (i.e., mathematical concepts, mental processes, and certain methods of organizing human activity).
The identified limitations of independent claim 9 (representative of independent claims 1 and 17) recite
one or more processing systems; and
one or more computer-readable media storing instructions which, when executed by the one or more processing systems, cause the system to perform operations comprising:
accessing a text transcript, the text transcript corresponding to an interaction between a first entity and a second entity, wherein the text transcript comprises a first number of tokens;
segmenting the text transcript into a plurality of portions, each portion of the plurality of portions comprises a second number of tokens less than the first number of tokens;
for each respective portion of the plurality of portions:
using a first machine-learning model to identify one or more entities included in the respective portion by providing a first prompt to the first machine- learning model, wherein a number of tokens associated with a context window of the first machine-learning model is less than the first number of tokens,
using a second machine-learning model to extract one or more facts from the respective portion based at least in-part on the one or more entities and by providing a second prompt to the second machine-learning model, wherein the second machine-learning model is different from the first machine-learning model, and wherein a number of tokens associated with a context window of the second machine-learning model is less than the first number of tokens, and
adding the one or more facts to a collection of facts;
using a plurality of third machine-learning model prompts to generate a set of note sections based at least in-part on the collection of facts, wherein each note section of the set of note sections corresponds to a section of a Subjective, Objective, Assessment and Plan (SOAP) note;
generating the SOAP note by combining note sections of the set of note sections; and
storing the SOAP note in a database associated with at least one of the first entity and the second entity
The identified limitations, under their broadest reasonable interpretation, cover performance of the limitations in the mind (including observation, evaluation, judgement or opinion) but for the recitation of generic computer components. That is, other than reciting processor, storage media, machine learning model (interpreted as computer), and database, nothing in the claim elements precludes the steps form practically being performed in the mind. For example, the identified limitations encompass a user (e.g., physician) writing and relaying entity (e.g., patient) information in a structured note format. The claim limitations fall within the Mental Processes groupings of abstract ideas. Thus, the claimed invention recites a judicial exception.
Part I: Step 2A, prong two: additional elements that integrate the judicial exception into a practical application
Under step 2A, Prong Two of the Alice framework, the claims are analyzed to determine whether the claims recite additional elements that integrate the judicial exception into a practical application. In particular, the claims are evaluated to determine if there are additional elements or a combination of elements that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claims are more than a drafting effort designed to monopolize the judicial exception.
This judicial exception is not integrated into a practical application. As a whole, the processor, storage media, and machine learning model, and database in the steps are 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 claim is directed to an abstract idea.
Dependent claims 2-8, 10-16, and 18-24, when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations fail to establish that the claims are not directed to an abstract idea. For instance, the dependent claims
Since these claims are directed to an abstract idea, the Office must determine whether the remaining limitations “do significantly more” than describe the abstract idea.
Part II. Determine whether any Element, or Combination, Amounts to“Significantly More” than the Abstract Idea itself
Under Part II, the steps of claims, when considered individually and as an ordered combination, do not improve another technology or technical field, do not improve the functioning of the computer itself, and are not enough to qualify as "significantly more". For example, the steps require no more than a conventional computer to perform generic computer functions. As noted in Prong Two, the processor, storage media, and machine learning model, and database in the steps are 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. Therefore, based on the two-part Mayo analysis, there are no meaningful limitations in the claim that transform the exception into a patent eligible application such that the claim amounts to significantly more than the exception itself. Claims 1-24, when considered individually and as an ordered combination, are rejected as ineligible subject matter under 35 U.S.C. 101.
Dependent claims 2-8, 10-16, and 18-24 when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional claims do no recite significantly more than an abstract idea.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Lipton et al. (US 20220375605 A1), Methods Of Automatically Generating Formatted Annotations Of Doctor-Patient Conversations
Lipton describes the automatic generation of formatted annotations of doctor-patient conversations using the Subjective, Objective, Assessment and Plan (SOAP) format including segmenting the accessing text transcripts. The prior art also describes using word-piece tokenization using BERT models. However, Lipton does not teach or suggest “using a first machine-learning model to identify one or more entities included in the respective portion by providing a first prompt to the first machine- learning model, wherein a number of tokens associated with a context window of the first machine-learning model is less than the first number of tokens, using a second machine-learning model to extract one or more facts from the respective portion based at least in-part on the one or more entities and by providing a second prompt to the second machine-learning model, wherein the second machine-learning model is different from the first machine-learning model, and wherein a number of tokens associated with a context window of the second machine-learning model is less than the first number of tokens” since the entities are already known and identified in the system of Lipton. Moreover, Lipton does not teach or suggest using named entity recognition model to identify the one or more entities as recited in dependent claims 3, 11, and 19.
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.
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/CHINYERE MPAMUGO/Primary Examiner, Art Unit 3685