DETAILED ACTION
Notice to Applicant
This communication is in response to the application submitted February 11, 2025. The present application is based upon and claims the benefit of priority from Japanese Patent Application No. 2024-024888 filed on February 21, 2024. Claims 1 – 10 are pending.
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 .
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(4) because reference character “202” has been used to designate both “Explanation of Therapy” and “Complaint/Question” in Figure 5. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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 – 10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step One
Claims 1 – 10 are drawn to a system, method, and computer-readable non-transitory recording medium, which is/are statutory categories of invention (Step 1: YES).
Step 2A Prong One
Independent claims 1, 9, and 10 recite a medical treatment comprising acquiring medical information regarding a patient, content information which indicates content of an exchange in a medical examination between the patient and a person examining the patient, and state information regarding feelings of the patient in the medical examination; generating explanatory text regarding a matter which is inferred to make the patient feel uneasy, the medical information, the content information, and the state information.
The recited limitations, as drafted, under their broadest reasonable interpretation, cover certain methods of organizing human activity, as reflected in the specification, by using speech to text information to more clearly explain to a patient the results of their medical examination, and providing the text to the patient. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or relationships or interactions between people, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. The present claims cover certain methods of organizing human activity because they “provide a technique for alleviating an uneasy feeling that a patient experiences in medical treatment”. (paragraph 6 of the published specification).. Accordingly, the claims recite an abstract idea(s) (Step 2A Prong One: YES).”
Step 2A Prong Two
This judicial exception is not integrated into a practical application. The claims are abstract but for the inclusion of the additional elements including:
Claim 1: “apparatus”, “at least one processor”, “language model”, “machine learning’, “outputting”
Claims 2, 5: “apparatus”, “at least one processor”
Claim 3: “apparatus”, “at least one processor”, “converts the speech data into the content information in text format”
Claim 4: “apparatus”, “at least one processor”, “speaker recognition based on the speech data and transcribes, speaker by speaker, what speakers say, to generate the content information which represents content of a speaker-by-speaker speech”
Claims 6 – 8: “apparatus”
Claim 9: “at least one processor”, “language model”, “machine learning’, “outputting”
Claim 10: “computer-readable non-transitory recording medium having recorded thereon a medical treatment assist program for causing a computer to function as a medical treatment assist apparatus”, “language model”, “machine learning’, “outputting”
These features are additional elements that are recited at a high level of generality such that they amount to no more than mere instruction to apply the exception using generic computer components. See: MPEP 2106.05(f).
The additional elements are merely incidental or token additions to the claim that do not alter or affect how the process steps or functions in the abstract idea are performed. Therefore, the claimed additional elements do not add meaningful limitations to the indicated claims beyond a general linking to a technological environment. See: MPEP 2106.05(h).
The combination of these additional elements is no more than mere instructions to apply the exception using generic computer components. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Hence, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Accordingly, the claims are directed to an abstract idea (Step 2A Prong Two: NO).
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, using the additional elements to perform the abstract idea amounts to no more than mere instructions to apply the exception using generic components. Mere instructions to apply an exception using a generic components cannot provide an inventive concept. See MPEP 2106.05(f).
Further, the claimed additional elements, identified above, are not sufficient to amount to significantly more than the judicial exception because they are generic components that are not integrated into the claim because they are merely incidental or token additions to the claim that do not alter or affect how the process steps or functions in the abstract idea are performed. Therefore, the claimed additional elements do not add meaningful limitations to the indicated claims beyond a general linking to a technological environment. See: MPEP 2106.05(h).
Further, the claimed additional elements, identified above, are not sufficient to amount to significantly more than the judicial exception because they are generic components that are configured to perform well-understood, routine, and conventional activities previously known to the industry. See: MPEP 2106.05(d). Said additional elements are recited at a high level of generality and provide conventional functions that do not add meaningful limits to practicing the abstract idea. The published specification supports this conclusion as follows:
[0073] Examples of the processor Cl can include a central processing unit (CPU), a graphic processing unit (GPU), a digital signal processor (DSP), a micro processing unit (MPU), a floating point number processing unit (FPU), a physics processing unit (PPU), a tensor processing unit (TPU), a quantum processor, a microcontroller, and a combination thereof. Examples of the memory C2 can include a flash memory, a hard disk drive (HDD), a solid state drive (SSD), and a combination thereof.
[0074] The computer C may further include a random access memory (RAM) into which the program P is loaded at the time of execution and in which various kinds of data are temporarily stored. The computer C may further include a communication interface via which data is transmitted to and received from another apparatus. The computer C may further include an input-output interface via which inputting- outputting equipment such as a keyboard, a mouse, a display, or a printer is connected.
[0075] The program P can be recorded on a non-transitory tangible recording medium M capable of being read by the computer C. Examples of such a recording medium M can include a tape, a disk, a card, a semiconductor memory, and a programmable logic circuit. The computer C can obtain the program P via such a recording medium M. The program P can be transmitted via a transmission medium. Examples of such a transmission medium can include a communication network and a broadcast wave. The computer C can obtain the program P also via such a transmission medium.
Viewing the limitations as an ordered combination, the claims simply instruct the additional elements to implement the concept described above in the identification of abstract idea with routine, conventional activity specified at a high level of generality in a particular technological environment.
Hence, the claims as a whole, considering the additional elements individually and as an ordered combination, do not amount to significantly more than the abstract idea (Step 2B: NO).
Dependent claim(s) 2 – 8 when analyzed as a whole, considering the additional elements individually and/or as an ordered combination, are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea without significantly more. These claims fail to remedy the deficiencies of their parent claims above, and are therefore rejected for at least the same rationale as applied to their parent claims above, and incorporated herein.
Claim Rejections - 35 USC § 102
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 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 – 2, 5, and 7 – 10 is/are rejected under 35 U.S.C. 102(a) as being anticipated by Kozloski et al., herein after Kozloski (U.S. Publication Number 2015/0100521 A1).
Claim 1. Kozloski teaches a medical treatment assist apparatus, comprising text
at least one processor (paragraph 16 discloses a processor operatively connected to the graphic user interface and biometric devices), the at least one processor carrying out:
an acquiring process of acquiring medical information regarding a patient, content information which indicates content of an exchange in a medical examination between the patient and a person examining the patient (paragraph 48 discloses a digital physician (DP) analyzes the inputs (textual) and determining a useful answer (diagnosis) via established question/answer techniques; paragraph 49 discloses the emotional state or personality type may be estimated by the system accessing a user's profile, by an assessment of natural language used by the person, by biometrics, by a history of previous interactions, by an analysis of word combinations used for similar users), and state information regarding feelings of the patient in the medical examination (paragraph 48 discloses analyzing and monitoring the emotional state of the patient (e.g. with user profile/query characteristics, biometrics, analysis of language, questionnaires, reports from nursing staff and family members, food intake information) to generate the emotional impact of the answer (feelings of patient); paragraph 49 discloses the emotional state or personality type may be estimated by the system accessing a user's profile, by an assessment of natural language used by the person, by biometrics, by a history of previous interactions, by an analysis of word combinations used for similar users);
an explanatory text generating process of generating explanatory text regarding a matter which is inferred to make the patient feel uneasy, with use of a language model generated by machine learning, the medical information, the content information, and the state information (Figures 1 and 2; paragraph 39 discloses methods for returning an answer to a query in an empathetic manner based on a determination that the answer may evoke a negative emotional state, such that the system determines whether the answer may invoke a negative user response (emotional state) and, if this occurs, provide the result in an empathetic manner; paragraph 42 discloses systems which answer natural language questions by querying data repositories and applying elements of language processing, information retrieval, and machine learning to arrive at a conclusion; paragraph 83 discloses when generating the output answers, the processor generates relatively more empathetic output answers or relatively less empathetic output answers based on the sensitivity level associated with the inquiry); and
an outputting process of outputting the explanatory text (paragraph 14 discloses automatically generating output answers to the inquiry based on the sensitivity level associated with the inquiry using the computerized device to refine the potential answers, such that when generating the output answers, the method can generate more empathetic output answers or relatively less empathetic output answers based on the sensitivity level associated with the inquiry; paragraph 67 discloses information of the patient’s emotional state can be output to healthcare professionals, where they can formulate strategies to present unfavorable information in such a way that minimizes stress, while benefiting the patient).
Claim 2. Kozloski teaches the medical treatment assist apparatus according to claim 1. Kozloski teaches wherein the at least one processor further carries out a feelings analyzing process of analyzing the feelings of the patient in the medical examination, and in the acquiring process, the at least one processor acquires the state information which includes an analysis result provided by the feelings analyzing process (paragraph 48 discloses a digital physician (DP) analyzes the inputs (textual) and determining a useful answer (diagnosis) via established question/answer techniques; paragraph 49 discloses the emotional state or personality type may be estimated by the system accessing a user's profile, by an assessment of natural language used by the person, by biometrics, by a history of previous interactions, by an analysis of word combinations used for similar users).
Claim 5. Kozloski teaches the medical treatment assist apparatus according to claim 1. Kozloski teaches wherein in the explanatory text generating process, the at least one processor refers to the state information to determine whether the patient is feeling uneasy, and generates the explanatory text in a case of a determination that the patient is feeling uneasy (paragraph 48 discloses analyzing and monitoring the emotional state of the patient (e.g. with user profile/query characteristics, biometrics, analysis of language, questionnaires, reports from nursing staff and family members, food intake information) to generate the emotional impact of the answer (feelings of patient); paragraph 49 discloses the emotional state or personality type may be estimated by the system accessing a user's profile, by an assessment of natural language used by the person, by biometrics, by a history of previous interactions, by an analysis of word combinations used for similar users).
Claim 7. Kozloski teaches the medical treatment assist apparatus according to claim 1. Kozloski teaches wherein the medical information includes at least one selected from the group consisting of personal information regarding the patient, information on findings shown by a medical examination performed on the patient, and medical history information regarding the patient (paragraph 48 discloses analyzing and monitoring the emotional state of the patient (e.g. with user profile/query characteristics, biometrics, analysis of language, questionnaires, reports from nursing staff and family members, food intake information) to generate the emotional impact of the answer (feelings of patient); paragraph 49 discloses the emotional state or personality type may be estimated by the system accessing a user's profile, by an assessment of natural language used by the person, by biometrics, by a history of previous interactions, by an analysis of word combinations used for similar users).
Claim 8. Kozloski teaches the medical treatment assist apparatus according to claim 1. Kozloski teaches wherein the explanatory text is used in decision-making by the patient regarding medical treatment (paragraph 45 discloses the question/answer systems may consider the assessed psychological states as inputs to the system used to suggest diagnoses and treatments to a healthcare provider).
Claim 9. Kozloski teaches a medical treatment assist method, comprising:
at least one processor (paragraph 16 discloses a processor operatively connected to the graphic user interface and biometric devices) acquiring medical information regarding a patient, content information which indicates content of an exchange in a medical examination between the patient and a person examining the patient (paragraph 48 discloses a digital physician (DP) analyzes the inputs (textual) and determining a useful answer (diagnosis) via established question/answer techniques; paragraph 49 discloses the emotional state or personality type may be estimated by the system accessing a user's profile, by an assessment of natural language used by the person, by biometrics, by a history of previous interactions, by an analysis of word combinations used for similar users), and state information regarding feelings of the patient in the medical examination (paragraph 48 discloses analyzing and monitoring the emotional state of the patient (e.g. with user profile/query characteristics, biometrics, analysis of language, questionnaires, reports from nursing staff and family members, food intake information) to generate the emotional impact of the answer (feelings of patient); paragraph 49 discloses the emotional state or personality type may be estimated by the system accessing a user's profile, by an assessment of natural language used by the person, by biometrics, by a history of previous interactions, by an analysis of word combinations used for similar users);
the at least one processor (paragraph 16 discloses a processor operatively connected to the graphic user interface and biometric devices) generating explanatory text regarding a matter which is inferred to make the patient feel uneasy, with use of a language model generated by machine learning, the medical information, the content information, and the state information (Figures 1 and 2; paragraph 39 discloses methods for returning an answer to a query in an empathetic manner based on a determination that the answer may evoke a negative emotional state, such that the system determines whether the answer may invoke a negative user response (emotional state) and, if this occurs, provide the result in an empathetic manner; paragraph 42 discloses systems which answer natural language questions by querying data repositories and applying elements of language processing, information retrieval, and machine learning to arrive at a conclusion; paragraph 83 discloses when generating the output answers, the processor generates relatively more empathetic output answers or relatively less empathetic output answers based on the sensitivity level associated with the inquiry); and
the at least one processor outputting the explanatory text (Figures 1 and 2; paragraph 39 discloses methods for returning an answer to a query in an empathetic manner based on a determination that the answer may evoke a negative emotional state, such that the system determines whether the answer may invoke a negative user response (emotional state) and, if this occurs, provide the result in an empathetic manner; paragraph 42 discloses systems which answer natural language questions by querying data repositories and applying elements of language processing, information retrieval, and machine learning to arrive at a conclusion; paragraph 83 discloses when generating the output answers, the processor generates relatively more empathetic output answers or relatively less empathetic output answers based on the sensitivity level associated with the inquiry).
Claim 10. Kozloski teaches a computer-readable non-transitory recording medium having recorded thereon a medical treatment assist program for causing a computer to function as a medical treatment assist apparatus (paragraph 23 discloses a tangible (non-transitory) computer-readable storage media can tangibly store instructions executable by a computerized device reading such instructions from the tangible computer-readable storage media), the medical treatment assist program causing the computer to carry out:
an acquiring process of acquiring medical information regarding a patient, content information which indicates content of an exchange in a medical examination between the patient and a person examining the patient (paragraph 48 discloses a digital physician (DP) analyzes the inputs (textual) and determining a useful answer (diagnosis) via established question/answer techniques; paragraph 49 discloses the emotional state or personality type may be estimated by the system accessing a user's profile, by an assessment of natural language used by the person, by biometrics, by a history of previous interactions, by an analysis of word combinations used for similar users), and state information regarding feelings of the patient in the medical examination (paragraph 48 discloses analyzing and monitoring the emotional state of the patient (e.g. with user profile/query characteristics, biometrics, analysis of language, questionnaires, reports from nursing staff and family members, food intake information) to generate the emotional impact of the answer (feelings of patient); paragraph 49 discloses the emotional state or personality type may be estimated by the system accessing a user's profile, by an assessment of natural language used by the person, by biometrics, by a history of previous interactions, by an analysis of word combinations used for similar users);
an explanatory text generating process of generating explanatory text regarding a matter which is inferred to make the patient feel uneasy, with use of a language model generated by machine learning, the medical information, the content information, and the state information (Figures 1 and 2; paragraph 39 discloses methods for returning an answer to a query in an empathetic manner based on a determination that the answer may evoke a negative emotional state, such that the system determines whether the answer may invoke a negative user response (emotional state) and, if this occurs, provide the result in an empathetic manner; paragraph 42 discloses systems which answer natural language questions by querying data repositories and applying elements of language processing, information retrieval, and machine learning to arrive at a conclusion; paragraph 83 discloses when generating the output answers, the processor generates relatively more empathetic output answers or relatively less empathetic output answers based on the sensitivity level associated with the inquiry); and
an outputting process of outputting the explanatory text (paragraph 14 discloses automatically generating output answers to the inquiry based on the sensitivity level associated with the inquiry using the computerized device to refine the potential answers, such that when generating the output answers, the method can generate more empathetic output answers or relatively less empathetic output answers based on the sensitivity level associated with the inquiry; paragraph 67 discloses information of the patient’s emotional state can be output to healthcare professionals, where they can formulate strategies to present unfavorable information in such a way that minimizes stress, while benefiting the patient).
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.
Claim(s) 3 – 4 and 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kozloski et al., herein after Kozloski (U.S. Publication Number 2015/0100521 A1) in view of Strom (U.S. Publication Number 2022/0019294 A1).
Claim 3. Kozloski teaches the medical treatment assist apparatus according to claim 1.
Kozloski fails to explicitly teach the following limitations met by Strom as cited:
wherein in the acquiring process, the at least one processor acquires speech data representing a speech picked up in the medical examination, and converts the speech data into the content information in text format (Figure 3; paragraph 11 discloses speech-to text conversion to create text data in electronic machine usable format; paragraph 35 discloses a device and method for a user to dictate speech remotely and have it converted into text entered on to a speech-to-text computing system, where the speech to text conversion takes place on an application within the speech to-text computing system (such as a smartphone)).
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to expand the method of Kozloski to further include a method and apparatus for remotely processing speech-to-text for entry onto a destination computing system as disclosed by Strom.
One of ordinary skill in the art, before the effective filing date of the claimed invention, would have been motivated to expand the method of Kozloski in this way by providing the ability to enter text by speech recognition through a device that processes the speech-to text-externally to the computer system but interfaces and appears as a generic HID device would be highly advantageous (Strom: paragraph 9).
Claim 4. Kozloski teaches the medical treatment assist apparatus according to claim 3.
Kozloski fails to explicitly teach the following limitations met by Strom as cited:
wherein in the acquiring process, the at least one processor carries out speaker recognition based on the speech data and transcribes, speaker by speaker, what speakers say, to generate the content information which represents content of a speaker-by-speaker speech (paragraph 48 discloses speech-to-text software is a class of software that takes audio content and transcribes it into written words in an electronic machine useable format, typically for further processing such as use in a word processor, on a display destination, or as executable commands by other software).
The motivation to combine the teachings of Kozloski and Strom is discussed in the rejection of claim 3, and incorporated herein.
Claim 6. Kozloski teaches the medical treatment assist apparatus according to claim 1.
Kozloski fails to explicitly teach the following limitations met by Strom as cited:
wherein the state information includes information which indicates at least one selected from the group consisting of a facial expression, a manner of speaking, a vital sign, and a feelings analysis result of the patient in the medical examination (paragraph 62 discloses the user speaks words, phrases, punctuation, sentences, or commands, which typically are available on an HID keyboard, as a voice input into the audio input device).
The motivation to combine the teachings of Kozloski and Strom is discussed in the rejection of claim 3, and incorporated herein.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Stegmann et al. (U.S. Publication Number 2024/0180482 A1) discloses systems and methods for digital speech-based evaluation of cognitive function.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KRISTINE K RAPILLO whose telephone number is (571)270-3325. The examiner can normally be reached Monday - Friday 7:30 - 4 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Fonya Long can be reached at 571-270-5096. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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KRISTINE K. RAPILLO
Examiner
Art Unit 3682
/K.K.R/Examiner, Art Unit 3682
Prosecution Insights