DETAILED ACTION
Status of Claims
This is the first office action on the merits in response to the application filed on 4 October 2024.
Claim(s) 1-20 are currently pending and have been examined.
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 .
Information Disclosure Statement
The information disclosure statement(s) (IDS(s)) submitted on 13 May 2025 is/are partially in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement(s) is/are being considered by the examiner as marked.
Priority
This application claims priority of IN Application No. 202341066971 filed on 6 January 2023. Applicant’s claim for the benefit of this prior filed application is acknowledged.
Claim Interpretation
Examiner notes that claims 1 recites a memory storing instructions that facilitate performance of a set of operations when executed. The broadest reasonable interpretation of facilitating a set of operations does not require the performance of the full set of operations, but instead requires only assisting a single operation. Thus the broadest reasonable interpretation of the claim only requires that the memory store instructions that when executed assist a single operation of the recited operation. Claim 20 is similarly interpreted.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claims not listed below are rejected for dependency.
Claim 1 recites “identifying a textual entities.” The article indicates that only one entity is required to be identified while the noun’s pluralization indicates that multiple entities must be identified. This ambiguity would make the scope of the claim unclear to one of ordinary skill in the art, rendering the claim indefinite. Claims 13 and 20 are similarly rejected. For the purposes of examination, the claim will be interpreted as requiring identifying only one textual entity.
Claim 11 recites “generating the textual content included in the report.” There is no antecedent basis for “textual content included in the report”, and it is unclear whether this limitation refers to the previously claimed “textual entities” or not. Because of this lack of clarity one of ordinary skill in the art would not be able to determine the boundaries of the claim, rendering the claim indefinite. Claims 12 and 19 are similarly rejected.
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 under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 13, which is representative of claims 1 and 20, recites: a method, comprising:
identifying,
determining,
providing,
receiving,
The preceding recitation of the claim has had strikethroughs applied to the additional elements beyond the abstract idea to more clearly demonstrate the limitations setting forth the abstract idea. The remaining limitations describe a concept of reviewing a document, providing an editing suggestion, and gathering feedback regarding the suggestion. This concept describes a mental process that an editor should follow to provide editing feedback similar to the “mental process that a neurologist should follow when testing a patient for nervous system malfunctions” given in MPEP 2106.04(a)(2)(II)(C) as an example of managing personal behavior in the methods of organizing human activity sub-grouping. As such, these limitation set forth a method of organizing human activity. Alternatively, the identified concept is analogous to the examples of “observation”, “evaluation”, and “judgement” given in MPEP 2106.04(a)(2)(III). Further, this concept as claimed does not require a scale of data beyond the mental faculties of a human being and the operations and can be performed in the human mind. As such, these limitation set forth a mental process. Therefore the claims are determined to recite an abstract idea.
MPEP 2106, reflecting the 2019 PEG, directs examiners at Step 2A Prong Two to consider whether the additional elements of the claims integrate a recited abstract idea into a practical application.
Claim 1 recites the additional element of a system, comprising: a processor; and a memory. Claim 13 recites the additional element of a system comprising at least one processor. Claim 20 recites the additional element of a non-transitory machine-readable medium. These additional elements are all recited at a very high level of generality, and are interpreted as generic computing devices used to implement the abstract idea. Per MPEP 2106.05(f), implementing an abstract idea with a generic computing device does not integrate an abstract idea into a practical application in Step 2A Prong Two, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea on a generic computer. As such, these additional elements do not integrate the abstract idea into a practical application.
The claims further recite the additional element of an artificial intelligence model and retraining the artificial intelligence model. The incorporation of this model and the retraining of it amounts to instructions to use a generic computing device to implement the abstract idea. As previously noted, such additional elements do not integrate an abstract idea into a practical application. As such, this additional element does not integrate the abstract idea into a practical application.
The claims further recite the additional elements of receiving user input via a graphical user interface and providing information via the graphical user interface. The reception and display of data with a graphical user interface is considered insignificant extra-solution activity to the identified abstract idea. As such, these additional elements do not integrate the abstract idea into a practical application.
There are no further additional elements. When considered as a combination, the additional elements only generally link the abstract idea and insignificant extra-solution activity to a technological environment of a computing device. As such, the combination of additional elements does not integrate the abstract idea into a practical application. Therefore because the additional elements, individually and as a combination, do not integrate the claims into a practical application, the claims are determined to be directed to an abstract idea.
At Step 2B of the Mayo/Alice analysis, examiners are to consider whether the additional elements amount to significantly more than the abstract idea.
As previously noted, the claims recite additional elements which may be interpreted as generic computing devices used to implement the abstract idea. However, per MPEP 2106.05(f), implementing an abstract idea on a generic computing device does not add significantly more in Step 2B, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea on a generic computer. As such, these additional elements do not amount to significantly more.
As previously noted, the claims recite additional elements receiving user input via a graphical user interface and providing information via the graphical user interface. However, Anderson et al. (US 2005/0010416 A1) demonstrates (“the device will provide conventional GUI dialogs for displaying information and obtaining input” [0125]) that such operations with a graphical user interface were conventional long before the priority date of the claimed invention. As such, As such, these additional elements do not amount to significantly more.
There are no further additional elements. When considered as a combination, the additional elements only generally link the abstract idea and insignificant extra-solution activity to a technological environment of a computing device. As such, the combination of additional elements does not amount to significantly more than the abstract idea. Therefore, when considered individually and as a combination, the additional elements of the independent claims do not amount to significantly more than the judicial exception. Thus the independent claims are not patent eligible.
Dependent claims 2-9, 11, 12 and 14-19 further describe the abstract idea, but the claims continue to recite an abstract idea albeit a narrowed one. Dependent claims 2-9, 12, and 14-18 recite no further additional elements. The previously identified additional elements, individually and as a combination, do not integrate the narrowed abstract idea for equivalent reasons as those provided above. Therefore these claims remain directed to an abstract idea. Additionally, the previously identified additional elements, individually and as a combination, does not amount to significantly more than the narrowed abstract idea for equivalent reasons as those provided above. Dependent claims 10, 11, and 19 further describe the additional element of the artificial intelligence model. However, the incorporation of these limitations continues to amount to instructions to implement the abstract idea with a generic computing device. As such, these additional elements, individually and in combination with the prior identified additional elements, do not integrate the abstract idea or the narrowed abstract idea for equivalent reasons as those provided above. Therefore these claims remain directed to an abstract idea. Additionally, these additional elements, individually and in combination with the prior identified additional elements, do not amount to significantly more than either the abstract idea or the narrowed abstract idea for equivalent reasons as those provided above. Because the dependent claims remain directed to an abstract idea without reciting significantly more, the dependent claims are not patent eligible.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-12 and 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kartoun et al. (US 2020/0321085 A1).
Regarding Claim 1 and 20: Kartoun discloses a system, comprising: a processor (See at least [0036]); and a memory (See at least [0036]) that stores executable instructions that, when executed by the processor, facilitate performance of operations, the operations comprising: identifying a textual entities in a medical report associated with a patient in association with receiving user input entering at least some of the textual entities into the report via a graphical user interface; determining edit recommendations related to one or more of the textual entities, where the edit recommendations are generated by an artificial intelligence model, and wherein the edit recommendation relate to possible errors or improvements based on information comprising medical history data of the patient, one or more clinical guidelines applicable to the report, and one or more medical ontologies; providing feedback information regarding the edit recommendations via the graphical user interface (In step 440, the suggestion system 340 determines a suggestion for providing to the user for modifying the clinical narrative note to improve one or more of the factor ratings. In one example, the suggestion system 340 may provide a suggestion for improving a completion score and/or a clarity score of the clinical narrative note. The suggestion system 340 may provide suggestions for missing information, improving unclear statements, resolving discrepancies, or correcting likely errors. In one example, the suggestion system 340 may provide suggested words for adding to or replacing part of a clinical narrative note. See at least [0055]. Examiner’s note: as explained above, the broadest reasonable interpretation of a claim to the facilitation of a set of operations does not require the performance of each operation of the set); receiving user feedback regarding selections related to the edit recommendations; and retraining the artificial intelligence model using the report and the user feedback as a training data, resulting in an updated version of the artificial intelligence model.
Regarding Claims 2-12: Kartoun discloses the above system facilitating a set of operations. Claims 2-12 further describe the operations facilitated by the system, but Kartoun’s system continues to facilitate the narrowed set of operations. As such, these claims are also anticipated by Kartoun.
Claim Rejections - 35 USC § 103
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.
Claim(s) 13-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kartoun et al. (US 2020/0321085 A1) in view of Sadeghi et al. (US 2014/0278448 A1).
Regarding Claim 13: Kartoun discloses a method, comprising:
identifying, by a system comprising at least one processor, a textual entities in a medical report associated with a patient in association with receiving user input entering at least some of the textual entities into the report via a graphical user interface (a user may enter notes via the notation assistant interface 135 and the notation processing system 320 may use natural language processing to extract information from the narrative notes. For example, the notation processing system 320 may extract objective information that is related to the patient's health. In one embodiment, the notation processing system 320 extracts terms that indicate symptoms (e.g., pain, fever, etc.), background (e.g., age, gender, ethnicity, etc.), appearance (pale, distressed, etc.), or physiological observations (e.g., blood pressure, heart rate, etc.). In another example, the notation processing system 320 may extract subjective information related to the physician's judgement or choice of words, such as adjectives, declarations, terms indicating opinion or fact, confidence levels, etc. See at least [0046]);
determining, by the system, edit recommendations related to one or more of the textual entities, and wherein the edit recommendations are generated by an artificial intelligence model, and wherein the edit recommendations relate to possible errors or improvements (In step 440, the suggestion system 340 determines a suggestion for providing to the user for modifying the clinical narrative note to improve one or more of the factor ratings. In one example, the suggestion system 340 may provide a suggestion for improving a completion score and/or a clarity score of the clinical narrative note. The suggestion system 340 may provide suggestions for missing information, improving unclear statements, resolving discrepancies, or correcting likely errors. In one example, the suggestion system 340 may provide suggested words for adding to or replacing part of a clinical narrative note. See at least [0055]. Also: The suggestion system 340 is configured to consider information that is part of a clinical narrative note (e.g., the objective and subjective information extracted by the notation processing system 320), determine what is missing or unclear, and provide suggestions for what information could be entered to improve the note. See at least [0048]. Also: the machine learning system 310 may train an ambiguity classifier based on known clear and unclear narrative notes. … an ambiguity classifier may be configured to determine how clearly the narrative note describes the information need to assess the heart health status. See at least [0051]);
providing, by the system, feedback information regarding the edit recommendations via the graphical user interface (In step 440, the suggestion system 340 determines a suggestion for providing to the user for modifying the clinical narrative note to improve one or more of the factor ratings. In one example, the suggestion system 340 may provide a suggestion for improving a completion score and/or a clarity score of the clinical narrative note. The suggestion system 340 may provide suggestions for missing information, improving unclear statements, resolving discrepancies, or correcting likely errors. In one example, the suggestion system 340 may provide suggested words for adding to or replacing part of a clinical narrative note. See at least [0055]);
receiving, by the system, user feedback regarding selections related to the edit recommendations; and retraining the artificial intelligence model using the report and the user feedback as a training data, resulting in an updated version of the artificial intelligence model (The data repository 350 may be a database configured to store data. The data repository 350 may be configured to receive data from the notation assistant system 110 and/or from one or more data sources 120 and store the data according to appropriate storage protocols. In some embodiments, the data repository 350 receives data from the notation assistant system 110, such as from the notation processing system 320 in order to improve the dataset usable by the machine learning system 310 for developing a classifier. See at least [0049]. Also: the machine learning system 310 may review clinical narrative notes (and optionally with additional structured variables such as laboratory measurements, comorbidities, medications, etc.) from the database 125 and use supervised or unsupervised learning to develop classifiers for scoring narrative notes. See at least [0043]).
Kartoun does not expressly disclose where the edit recommendations are based on information comprising medical history data of the patient, one or more clinical guidelines applicable to the report, and one or more medical ontologies.
Sadeghi teaches edit recommendations based on information comprising medical history data of a patient, one or more clinical guidelines applicable to the report, and one or more medical ontologies (one or more alerts triggered at act A615 may be provided to a user interface component (e.g., the illustrative QA user interface A125 shown in FIG. 1) at act A620 to be displayed to the user. The alerts may be provided in any suitable form. For example, in some embodiments, an alert may include a corresponding portion of the CLU engine output, which may in turn include one or more portions of report text that were identified by the CLU engine as representing an error or critical result, and/or locations of such text in the report. See at least [0117]. Also: an alert may be provided when a set of one or more clinical facts is collected from a patient encounter, and it is determined that a diagnosis that was not specified in the set of facts may possibly be ascertained from the patient encounter. In one example, such an unspecified diagnosis may be a known comorbidity of a diagnosis that was included in the set of facts. In another example, the unspecified diagnosis may be a known complication of a procedure or diagnosis included in the set of facts. In yet another example, the unspecified diagnosis may be an identification of the fact that a diagnosis included in the set of facts is actually a complication of a procedure or other diagnosis included in the set of facts, or of a procedure or other diagnosis included in facts from the patient's history prior to the current encounter. Similarly, the unspecified diagnosis may be an identification of the fact that a diagnosis included in facts from the patient's previous history is a complication of a diagnosis ascertained during the current patient encounter. In some embodiments, when the possibility or likelihood of such an unspecified diagnosis is determined from the original set of facts collected from the patient encounter, an alert may query the user (e.g., the clinician or another user) as to whether the unspecified diagnosis should be ascertained from the patient encounter. See at least [0140]. Also: alerts may be provided for contraindications related to a combination of a medication with an allergy, a medication with a diagnosis, a medication with a patient's age or gender, a medication with a condition indicated in the patient's history, a medical procedure with any of the foregoing characteristics, or any other combination of a planned treatment with another clinical fact from the current patient encounter or from the patient's history for which the planned treatment is known to be contraindicated. See at least [0141]. Also: an ontology linked to medical terms may be used by a CLU engine in some embodiments and may facilitate identifying errors and/or critical results in a medical report. For instance, with respect to the example shown in FIG. 5, an ontology may indicate that the two terms "total hip antroplasty" and "THA" refer to the same concept in the ontology. See at least [0100]).
Kartoun provides a system that makes suggestions for modifying clinical notes, upon which the claimed invention’s use of various information to generate the suggestions can be seen as an improvement. However, Sadeghi demonstrates that the prior art already knew of using the claimed types of information to generate suggestions for modifications to clinical documentation. One of ordinary skill in the art could have easily incorporated the techniques of Sadeghi into the system of Kartoun. Further, one of ordinary skill in the art would have recognized that such an application of Sadeghi would have resulted in an improved recommendations. As such, the application of Sadeghi and the claimed invention would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention in view of the disclosures of Kartoun and the teachings of Sadeghi.
Regarding Claim 14: Kartoun in view of Sadeghi teaches the above limitations. Kartoun further discloses wherein the errors or improvements comprise are based on the one or more textual entities being clinically incorrect (The suggestion system 340 may provide suggestions for missing information, improving unclear statements, resolving discrepancies, or correcting likely errors. See at least [0055]).
Regarding Claim 15: Kartoun in view of Sadeghi teaches the above limitations. Sadeghi further teaches wherein the errors or improvements are based on the one or more textual entities being incompatible with the one or more clinical guidelines (the fact review system may access both facts collected from a current patient encounter and facts from the patient's historical records to determine whether alerts should be generated. In some embodiments, an alert to a conflict may be triggered by a combination of facts, at least one of which does not correspond to a medication. For example, alerts may be provided for contraindications related to a combination of a medication with an allergy, a medication with a diagnosis, a medication with a patient's age or gender, a medication with a condition indicated in the patient's history, a medical procedure with any of the foregoing characteristics, or any other combination of a planned treatment with another clinical fact from the current patient encounter or from the patient's history for which the planned treatment is known to be contraindicated. See at least [0141]). The motivation to combine Kartoun and Sadeghi is the same as explained under claim 13 above, and is incorporated herein.
Regarding Claim 16: Kartoun in view of Sadeghi teaches the above limitations. Sadeghi further teaches wherein the errors or improvements are based on the one or more textual entities being incompatible with the one or more medical ontologies (the fact review system may access both facts collected from a current patient encounter and facts from the patient's historical records to determine whether alerts should be generated. In some embodiments, an alert to a conflict may be triggered by a combination of facts, at least one of which does not correspond to a medication. For example, alerts may be provided for contraindications related to a combination of a medication with an allergy, a medication with a diagnosis, a medication with a patient's age or gender, a medication with a condition indicated in the patient's history, a medical procedure with any of the foregoing characteristics, or any other combination of a planned treatment with another clinical fact from the current patient encounter or from the patient's history for which the planned treatment is known to be contraindicated. See at least [0141]). The motivation to combine Kartoun and Sadeghi is the same as explained under claim 13 above, and is incorporated herein.
Regarding Claim 17: Kartoun in view of Sadeghi teaches the above limitations. Sadeghi further teaches wherein the errors or improvements are based on the one or more textual entities being inconsistent or incompatible with the medical history data of the patient (the fact review system may access both facts collected from a current patient encounter and facts from the patient's historical records to determine whether alerts should be generated. In some embodiments, an alert to a conflict may be triggered by a combination of facts, at least one of which does not correspond to a medication. For example, alerts may be provided for contraindications related to a combination of a medication with an allergy, a medication with a diagnosis, a medication with a patient's age or gender, a medication with a condition indicated in the patient's history, a medical procedure with any of the foregoing characteristics, or any other combination of a planned treatment with another clinical fact from the current patient encounter or from the patient's history for which the planned treatment is known to be contraindicated. See at least [0141]). The motivation to combine Kartoun and Sadeghi is the same as explained under claim 13 above, and is incorporated herein.
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kartoun et al. (US 2020/0321085 A1) in view of Sadeghi et al. (US 2014/0278448 A1), and further in view of Vagell et al. (US 9495341 B1).
Regarding Claim 18: Kartoun in view of Sadeghi teaches the above limitations. Kartoun does not expressly disclose wherein the feedback information comprises auxiliary information regarding a basis of the errors or improvements and wherein the auxiliary information comprises one or more links to a relevant portion of the one or more clinical guidelines or the medical history data. However, Vagell teaches wherein feedback information comprises auxiliary information regarding a basis of the errors or improvements and wherein the auxiliary information comprises one or more links to a relevant portion of data (The menu 208 can also include a reference element. The reference element can include a portion or snippet of the accurate factual proposition used to provide the text within the correction element. In the example in FIG. 2, the reference element includes reference link 214 “From WebAnswer Example” and the text snippet 216 “By definition, a baseball is ‘9 to 9.25 inches or 22.85 to 23.495 centimeters in circumference.’” The drafter of the electronic document can select the reference link 214 within the reference element to be directed to the source of the information in the correction element. See at least Column 5, Lines 14-36).
Kartoun and Sadeghi suggest a system that makes resourced based suggestions for modifying clinical notes, upon which the claimed invention’s provision of a link to a resource with a suggestion can be seen as an improvement. However, Vagell demonstrates that the prior art already knew of editing suggestion systems that provided links to resources supporting editing suggestions. One of ordinary skill in the art could have trivially applied the techniques of Vagell to the system of Kartoun and Sadeghi. Further, one of ordinary skill in the art would have recognized that such an application of Vagell would have resulted in an improved system providing a superior user experience by allowing users to access resources supporting the editing suggestions. As such, the application of Vagell and the claimed invention would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention in view of the disclosures of Kartoun and the teachings of Sadeghi and Vagell.
Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kartoun et al. (US 2020/0321085 A1) in view of Sadeghi et al. (US 2014/0278448 A1), and further in view of Rockne et al. (US 2024/0355437 A1).
Regarding Claim 19: Kartoun in view of Sadeghi teaches the above limitations. Additionally, Kartoun discloses associating one or more visual indicators with textual content indicating a measure of confidence pertaining to an accuracy level of the textual content; receiving additional user feedback regarding the textual content, the additional user feedback comprising an acceptance of the textual content, a rejection of the textual content or a revision to the textual content (The user interface 800 provides a suggestion for improving a clarity score. For instance, the user interface 800 highlights a phrase 805 that may be ambiguous and provides several options in a suggestion field 810 for the user to replace the ambiguous phrase 805 in a manner that would make the narrative more clear. For instance, instead of saying “some degree of congestive heart failure” the use may select that “the heart is decompensated.” See at least [0067]); and retraining the model using the report and the additional user feedback as training data (The data repository 350 may be a database configured to store data. The data repository 350 may be configured to receive data from the notation assistant system 110 and/or from one or more data sources 120 and store the data according to appropriate storage protocols. In some embodiments, the data repository 350 receives data from the notation assistant system 110, such as from the notation processing system 320 in order to improve the dataset usable by the machine learning system 310 for developing a classifier. See at least [0049]. Also: the machine learning system 310 may review clinical narrative notes (and optionally with additional structured variables such as laboratory measurements, comorbidities, medications, etc.) from the database 125 and use supervised or unsupervised learning to develop classifiers for scoring narrative notes. See at least [0043]).
Kartoun does not expressly disclose generating, by the system, the textual content included in the report based on the medical history data and using a generative large language model.
Rockne teaches generating, by the system, textual content included in a report based on medical history data and using a generative large language model (FIG. 3 depicts an example workflow 300 for generating summarized clinical data using machine learning, according to one embodiment of the present disclosure. See at least [0054]. Also: In the illustrated example, patient records 220 are accessed and evaluated by a text ML component 305 (e.g., using a text machine learning model) to generate text data 310. See at least [0056]. Also: the extraction ML component 315 may use keyword searching and/or machine learning model-based evaluations, such as processing the text data 310 using one or more large language models. See at least [0057]).
Kartoun and Sadeghi suggest a system that makes resourced based suggestions for modifying clinical notes, upon which the claimed invention’s generation of clinical notes can be seen as an improvement. However, Rockne demonstrates that the prior art already knew of generating clinical notes using large language models. One ordinary skill in the art could have easily applied the techniques of Rockne within the editing system of Kartoun and Sadeghi. Further, one of ordinary skill in the art would have recognized that such an application of Rockne would have resulted in a system which would automatically generate clinical notes and then work assist a user in editing those clinical notes. As such, the application of Rockne and the claimed invention would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention in view of the disclosures of Kartoun and the teachings of Sadeghi and Rockne.
Additional Considerations
The prior art made of record and not relied upon that is considered pertinent to applicant’s disclosure can be found in the PTO-892 Notice of References Cited.
Cao et al. (US 10740561 B1) provides an in-depth discussion of identifying entities in medical text.
Gaidylo et al. (US 1233247 B1) and Chiba et al. (US 2017/02205636 A1) provide further examples of graphical user interfaces for performed machine assisted text editing.
Rajan et al. (US 2018/0107792 A1) provides additional medical document error detection techniques.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Bion A Shelden whose telephone number is (571)270-0515. The examiner can normally be reached M-F, 12pm-10pm EST.
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, Kambiz Abdi can be reached at (571) 272-6702. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Bion A Shelden/ Primary Examiner, Art Unit 3685 2026-01-10