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
This Final Office Action is in response to the Amendment and Remarks filed on 04/06/2026. Claim 11 is new and claims 1-11 are pending and considered herein.
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 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without practical application and without significantly more than the abstract idea.
Claim 11 recites the following, wherein the abstract limitations are not emboldened:
A system for evaluating cognitive behavioral therapy messages, comprising: a patient messaging system; a therapist reply system; a database for storing, according to diagnosis, message and reply histories received from the patient messaging system and the therapist reply system for a plurality of patients; a computer in communication with the patient messaging system and the therapist reply system, said computer having access to the database; software executing on the computer for analyzing a message history for a particular patient to determine improvement or regression over time and/or over volume of communications through the patient messaging system and the therapist reply system; and software executing on the computer for ranking therapists by diagnosis and providing samples of higher ranked replies, and wherein the software for ranking therapists implements a semantic analysis technique on a plurality of sequences of messages and replies, each of the sequences being associated with a patient and a therapist.
Claim 1 recites substantially the same limitations. The claimed invention is broadly directed to the abstract idea of collecting patient information, analyzing the information, and determining different results based on the analyses using a data processing system.
The claims recite subject matter which recite steps of “evaluating cognitive behavioral therapy messages, for a plurality of patients; storing, according to diagnosis, message and reply histories received from the patient; analyzing a message history for a particular patient to determine improvement or regression over time and/or over volume of communications through the patient messaging system and the therapist reply system; and ranking therapists by diagnosis and providing samples of higher ranked replies, and wherein ranking therapists implements a semantic analysis technique on a plurality of sequences of messages and replies, each of the sequences being associated with a patient and a therapist” that as drafted, under the broadest reasonable interpretation, includes methods of organizing human activity including following rules or instructions. The claims are directed to matching a patient based on patient message information with a therapist and therapist replies. The claim recites as a whole a method of organizing human activity because the limitations include a user accessing rankings of therapists based on diagnosis and patient messages and therapist replies. This is a method of managing interactions between people. The mere nominal recitation of a generic computer system, a patient messaging system, a therapist reply system and database does not take the claims out of the method of organizing human interactions grouping. The limitations seem to monopolize the abstract idea of patient/caregiver analysis and care coordination and general diagnostic techniques between a clinician and her patient. Thus, the claims recite an abstract idea.
Additionally, the limitations of the independent claims could be considered an abstract idea including mental processes, whereby the steps of the claimed invention could be performed in the mind by manually obtaining patient messaging and therapist reply information and determining ranked therapists by diagnosis and samples of higher ranked replies. For example, but for the generic computing device language, a method for ranking therapists using replies and patient messages, in the context of this claim encompasses one skilled in the pertinent art to manually determine the details of performance and certification of a healthcare task. Other than reciting a generic computer system, a patient messaging system, a therapist reply system and a database nothing in the claim elements precludes the step from practically being performed in the mind. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind 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.
This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of a system, a patient messaging system, a therapist reply system, a database and computer, and the devices in these steps are recited at a high-level of generality (i.e., as a generic processor/server/storage/display/sensor performing a generic computer function of receiving inputs and displaying selected information) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, the 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. This judicial exception is not integrated into a practical application. In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to mere instructions to apply an exception (such as recitation of a data processing system comprising memory and one or more processors amounts to invoking computers as a tool to perform the abstract idea, see MPEP 2106.05(f)); or add insignificant extra-solution activity to the abstract idea. See MPEP 2106.05(g)). The claim is thus directed to an abstract idea.
Furthermore, the claim does 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, the additional elements of a system, a patient messaging system, a therapist reply system and a database amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
The dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims. Claims 2-4 describe semantic analysis techniques, which are recited at a high level of generality and even in combination do not provide a practical application or significantly more than the abstract idea. Claims 5-9 provides more detail for a ranking for therapists and analyzing of messages and further limits the abstract idea. Claim 10 details a computer to generate synthetic training data, which is recited at a high level of generality and even in combination do not provide a practical application or significantly more than the abstract idea The independent and dependent claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception, and add insignificant extra-solution activity to the abstract idea. For at least the reasons as stated above, the claims are not patent eligible under 35 U.S.C. §101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claims 1-2, 7 and 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. 2021/0391083 A1 to Moturu et al., hereinafter “Moturu ‘083,” in view of U.S. 2025/0022573 A1 to Darcy et al., hereinafter “Darcy,” in view of U.S. 11,995,696 B2 to Olds, hereinafter “Olds” and further in view of U.S. 2021/0090691 A1 to McNeil et al., hereinafter “McNeil.”
Regarding claim 1, Moturu ‘083 discloses A system for evaluating cognitive behavioral therapy messages, comprising: a patient messaging system; a therapist reply system (See Motoru ‘083 at least at Abstract; Paras. [0023] (“[R]eceiving a log of use dataset associated with patient digital communication behavior at a mobile computing device […] evaluating patient improvement.”), [0028], [0035]-[0041], ]0077] (digital conversation), [0146]-[0149]; Figs. 1-3, 19); a computer in communication with the patient messaging system and the therapist reply system, said computer having access to the database; software executing on the computer for analyzing a message history for a particular patient to determine improvement or regression over time and/or over volume of communications through the patient messaging system and the therapist reply system (See Motoru ‘083 at least at Abstract; Paras. [0023] (“[R]eceiving a log of use dataset associated with patient digital communication behavior at a mobile computing device […] evaluating patient improvement.”), [0028], [0035]-[0041], [0146]-[0149]; Figs. 1-3, 19).
Moturu ’083 may not specifically describe but Darcy teaches a database for storing, according to diagnosis, message and reply histories received from the patient messaging system and the therapist reply system for a plurality of patients (See Darcy at least at Paras. [0128]-[0132]; Figs. 1, 5-8).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the disclosure of Moturu ‘083 to incorporate the teachings of Darcy and provide analyzing message histories. Darcy is directed to an LLM conversation engine for treating symptoms of a mental health disorder. Incorporating the conversation engine of Darcy with the providing health therapeutic interventions to a user of Moturu ‘083 would thereby improve the communication between a patient and caregiver.
The references may not specifically describe but Olds teaches software executing on the computer for ranking therapists by diagnosis (See Olds at least at Col. 6, ln. 40 – Col. 7, ln. 63 (Responses on a sliding scale, ranked preferences, etc.) (“Semantic differential items […] In a non-limiting example, when calculating a match score for a single question the service outcome optimization system may compare the client's response to the responses of all therapist profiles. Since there will be a symmetry between the client's answer and the therapist's answer, initially, a statistics based matching algorithm is utilized that can calculate the root mean squared difference between the client's preference for an attribute and a therapist's self-description of an attribute. This process assumes that a stronger agreement in the preference of a client and the self-reported agreement to that preference by a therapist results in a stronger match […] once enough training data has been collected, the service outcome optimization system [including recommended therapy/treatment type, i.e., diagnosis, with strengths of therapist] will transition from using a simplistic statistics-based matching approach to a machine learning and deep learning approach to better match a client with a therapist); Col. 9, ln. 47 – Col. 10, ln. 60 (“The service outcome optimization system may generate a list of therapists for the client to review. These therapists are ranked according to their match score with the client […] The client is able to review profiles for each therapist before selecting a therapist to engage […] better recognize matches to create better treatment outcomes and provide predictions and recommendations for such matches.” Ranked therapists and best treatments and the client is able to review these therapists before selecting a therapist to engage, i.e., feedback for ranked therapists and match scores that are an ordered list.); Col. 13, ln. 59-67 (“[C]linicians ranked based on the match scores between them and a collection of actual poorly matched clients or the degree of match between clinician applicants and the prototypical poorly matched client.”); Col. 15, ln. 8-41 (“a client interface to permit a user to open and complete an intake questionnaire completing questions about demographics, issues and identities, and personality of the client. At 102 a professional service provider, such as in non-limiting examples, clinicians, salespersons, supervisory and administrative personnel, and other professionals, completes an intake questionnaire to select all concerns for which the therapist may have treatment experience and expertise.”); Col. 17, ln. 35-44 (“[U]pon statistical analysis by the service outcome optimization system, the platform may be able to demonstrate that the clinician has more desirable outcomes (for example, higher therapeutic alliance scores).”); Col. 18, ln. 64 – Col. 19, ln. 26 (Match scores are interpreted as replies and include responses and other preferences of patients.); Figs. 1-6).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the disclosure of Moturu ‘083 and Darcy to incorporate the teachings of Olds and provide ranked therapists by diagnosis and their applicability as a match for a patient to review. Olds is directed to improving service outcomes for patients and therapists using AI models. Incorporating the AI services for patients and therapists as in Olds with the conversation engine of Darcy and the providing health therapeutic interventions to a user of Moturu ‘083 would thereby improve the screening and subsequent matching for a patient and therapist.
The references may not specifically describe but McNeil teaches providing samples of higher ranked replies (See McNeil at least at Abstract (“The medical condition-based QA system processes a natural language input question about a patient to generate a set of candidate answers with an initial ranking of the candidate answers […] A response ranking component ranks candidate answers in the set of candidate answers based on the matching of content indicators of the medical condition content indicator data structures to the portions of content associated with the candidate answers to generate re-ranked candidate answers having a modified ranking.”); Paras. [0037]-[0042] (“[T]he cognitive system 100 provides a response to users in a ranked list of candidate responses while in other illustrative embodiments, the cognitive system 100 provides a single final response or a combination of a final response and ranked listing of other candidate responses.”), [0065]-[0068] (“Candidate response ranking engine 320 correlates the medical conditions associated with the user with medical conditions for which data structures have been defined that specify the particular terms/phrases, metadata, or other indicators of content that are indicative of content of particular interest to users having the corresponding medical conditions.”), [0087], [0091]-[0094]; Claim 4; Figs. 1-8).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the disclosure of Moturu ‘083, Darcy and Olds to incorporate the teachings of McNeil and provide ranked replies. McNeil is directed to a candidate response ranking based on personal medical condition. Incorporating the patient response ranking as in McNeil with the AI services for patients and therapists as in Olds, the conversation engine of Darcy and the providing health therapeutic interventions to a user of Moturu ‘083 would thereby improve the screening and subsequent matching for a patient and therapist.
Regarding claim 2, Moturu ‘083 as modified by Darcy, Olds and McNeil discloses the limitations of claim 1 and Olds further teaches wherein the software for ranking therapists implements a semantic analysis technique on a plurality of sequences of messages and replies, each of the sequences being associated with a patient and a therapist (See Olds at least at Col. 6, ln. 27 – Col. 7, ln. 3 (questions asked and answers receive from a patient based on the patient’s needs and clinical concerns); Col. 7, ln. 9-63 (“Semantic differential items […] In a non-limiting example, when calculating a match score for a single question the service outcome optimization system may compare the client's response to the responses of all therapist profiles. Since there will be a symmetry between the client's answer and the therapist's answer, initially, a statistics based matching algorithm is utilized that can calculate the root mean squared difference between the client's preference for an attribute and a therapist's self-description of an attribute. This process assumes that a stronger agreement in the preference of a client and the self-reported agreement to that preference by a therapist results in a stronger match.” Questions and answers between a therapist and patient); Col. 9, ln. 47 – Col. 10, ln. 60 (ranked therapists and the client is able to review these therapists before selecting a therapist to engage, i.e., feedback for ranked therapists.); Col. 15, ln. 8-41 (“a client interface to permit a user to open and complete an intake questionnaire completing questions about demographics, issues and identities, and personality of the client. At 102 a professional service provider, such as in non-limiting examples, clinicians, salespersons, supervisory and administrative personnel, and other professionals, completes an intake questionnaire to select all concerns for which the therapist may have treatment experience and expertise.”); Figs. 1-6)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the disclosure of Moturu ‘083, McNeil and Darcy to incorporate the teachings of Olds and provide a semantic analysis technique. Olds is directed to improving service outcomes for patients and therapists using AI models. Incorporating the AI services for patients and therapists as in Olds with the patient response ranking as in McNeil, the conversation engine of Darcy and the providing health therapeutic interventions to a user of Moturu ‘083 would thereby improve the screening and matching for a patient’s needs and treatment by a therapist.
Regarding claim 7, Moturu ‘083 as modified by Darcy, Olds and McNeil discloses the limitations of claim 1 and Olds further teaches wherein the software for ranking therapists analyzes the message history using a semantic technique to assess each reply against key attributes of therapeutic praxis, said attributes including at least two of: engaging, helpful, language, empathic, actionable, relevant, accurate, appropriate, accepting, clear, empowering (See Olds at least at Col. 7, ln. 9 – Col. 8, ln. 16 (“Semantic differential items […] Clients then are asked to rate each of their selected identities in response to the question: “How important is it to find a therapist who shares or has a deep understanding of (insert identity here) issues.” Responses are recorded on a slider scale, discretized as floating point numbers from 0, no importance, to 1, most important, in increments of 0.01 with the midpoint at 0.5. The responses may be recorded as “Not very important” for low integer values through “Somewhat important”, for mid-range integer values, to “Extremely important”, for high integer values. Personality section: Includes two subsections. Subsection 1 includes general personality questions. These questions are answers on a slider discretized as floating point numbers from 0, no importance, to 1, most important, in increments of 0.01 with the midpoint at 0.5. These questions are designed to allow the client to express preferences. Subsection 2 uses semantic differential items. These are pairings of words or phrases that are opposites but which could also both be desirable traits in a therapist. In a non-limiting example, to facilitate the collection of this information the client may be shown the prompt: “I would prefer a therapist who is .sub.——————” and then shown a slider with “Supportive” on one end and “Challenging” on the other and the response to the prompt from the client is collected and stored in the data file associated with the client. In an embodiment, therapists also complete an intake questionnaire that closely mirrors the one completed by clients. In a non-limiting example, clients may be asked to select all concerns that are motivating them to seek therapy. Therapists may be asked to select all concerns for which the therapist may have treatment experience and expertise. In a non-limiting example, a Therapist may be shown the prompt: “I would describe my therapeutic style as .sub.——————” and then also shown a slider with “Supportive” on one end and “Challenging” on the other for entry of their response. The Therapists response is collected and stored in a therapist profile data file associated with that particular Therapist.”); Figs. 1-6).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the disclosure of Moturu ‘083, McNeil and Darcy to incorporate the teachings of Olds and provide a semantic analysis technique. Olds is directed to improving service outcomes for patients and therapists using AI models. Incorporating the AI services for patients and therapists as in Olds with the patient response ranking as in McNeil, the conversation engine of Darcy and the providing health therapeutic interventions to a user of Moturu ‘083 would thereby improve the screening and subsequent matching for a patient and treatment by a therapist.
Regarding claim 10, Moturu ‘083 as modified by Darcy, Olds and McNeil discloses the limitations of claim 1 and Olds further teaches wherein the software executing on the computer is adapted to generate synthetic training data for the patient messaging system and/or the therapist reply system (See Olds at least at Col. 7, ln. 9 – Col. 8, ln. 16 (“Since there will be a symmetry between the client's answer and the therapist's answer, initially, a statistics based matching algorithm is utilized that can calculate the root mean squared difference between the client's preference for an attribute and a therapist's self-description of an attribute. This process assumes that a stronger agreement in the preference of a client and the self-reported agreement to that preference by a therapist results in a stronger match. This statistics-based approach is one method for addressing the “cold start” problem encountered in ML/deep learning systems where initially there is inefficient training data. Later on, once enough training data has been collected, the service outcome optimization system will transition from using a simplistic statistics-based matching approach to a machine learning and deep learning approach to better match a client with a therapist based on the identification of previously unidentified latent variables and through the discovery of non-linear relationships between variables.” Synthetic training data used initially); Figs. 1-6).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the disclosure of Moturu ‘083, McNeil and Darcy to incorporate the teachings of Olds and provide synthetic training data. Olds is directed to improving service outcomes for patients and therapists using AI models. Incorporating the AI services for patients and therapists as in Olds with the patient response ranking as in McNeil, the conversation engine of Darcy and the providing health therapeutic interventions to a user of Moturu ‘083 would thereby improve the patient and therapist communication, ranking and matching.
Regarding claim 11, claim 11 recites the same limitations included in claims 1 and 2 and is rejected under the same grounds of rejection and for the same reasoning as applied to claims 1 and 2, above.
Claims 3 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Moturu ‘083, in view Darcy, in view of Olds, in view of McNeil and further in view of U.S. 2024/0050003 A1 to Day, hereinafter “Day.”
Regarding claim 3, Moturu ‘083 as modified by Darcy, Olds and McNeil discloses the limitations of claim 2, and may not specifically describe but Day teaches wherein the semantic analysis technique is latent semantic analysis (LSA) (See Day at least at Para. [0073], [0124], [0138]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the disclosure of Moturu ‘083, Darcy, McNeil and Olds to incorporate the teachings of Day and provide analyzing using a semantic technique including LSA. Day is directed to validating user responses and a chatbot. Incorporating the user response validation of Day with the patient response ranking as in McNeil, the AI services for patients and therapists as in Olds, the conversation engine of Darcy and the providing health therapeutic interventions to a user of Moturu ‘083 would improve the matching and ranking of therapists and patients.
Regarding claim 8, Moturu ‘083 as modified by Darcy, Olds and McNeil discloses the limitations of claim 1, and may not specifically describe but Day teaches wherein the software for ranking therapists analyzes the message history using a semantic technique to assess at least one of the patient’s emotional spectrum, development, and activation (See Day at least at Abstract; Paras. [0138], [0166]; Figs. 16-19).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the disclosure of Moturu ‘083, Darcy, McNeil and Olds to incorporate the teachings of Day and provide analyzing using a semantic technique to assess emotion. Day is directed to validating user responses and a chatbot. Incorporating the user response validation of Day with the patient response ranking as in McNeil, the AI services for patients and therapists as in Olds, the conversation engine of Darcy and the providing health therapeutic interventions to a user of Moturu ‘083 would thereby advance the communications and screening for a patient and therapist.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Moturu ‘083, in view Darcy, in view of Olds, in view of McNeil and further in view of U.S. 2020/0005929 A1 to Tablan et al., hereinafter “Tablan.”
Regarding claim 4, Moturu ‘083 as modified by Darcy, Olds and McNeil discloses the limitations of claim 2 may not specifically describe but Tablan teaches wherein the semantic analysis technique uses semantic space theory (SST) (See Tablan at least at Para. [0111]-[0117] (“The vectorisation may allow deep learning processes to reason in semantic space rather than words space.”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the disclosure of Moturu ‘083, Darcy, McNeil and Olds to incorporate the teachings of Tablan and provide analyzing using a semantic technique including SST. Tablan is directed to a psychotherapy triage method and related services. Incorporating the psychotherapy triage method of Tablan with the patient response ranking as in McNeil, the AI services for patients and therapists as in Olds, the conversation engine of Darcy and the providing health therapeutic interventions to a user of Moturu ‘083 would improve the matching and ranking of therapists and prospective patients.
Claims Free from Prior Art
Claims 5-6 and 9 are free of the prior art. The references fail to specifically disclose alone or in combination “wherein the software for ranking therapists analyzes the message history to assess a patient's state, development, and/or progress in therapy,” of claim 5, “wherein the software ranks a plurality of therapists based on respective assessments of state, development, and/or progress in therapy for one or more patients associated with each of the plurality of therapists” of claim 6, and “wherein the software for ranking therapists provides higher ranked or higher rated therapist responses as feedback to the therapist reply system” of claim 9. U.S. 2026/0024525 A1 to Rollwage et al. is for a dialogue system between patient and therapist to recommend and rank interventions, and explains at Paras. [0167] (patient replies taken as input), [0267]-[0269] (recommender module), [0278], [0283]-[0287] (replies to questions), [0551]-[0553] a ranking of interventions used previously by therapists in response to patient inputs (messages sent and received) and Figs. 4-10. Moturu, Olds, Darcy, McNeil and Day teach similar techniques for improving care and recommendations between patient and caregiver/therapist, but not the narrow and specific rankings and analyses as claimed. There is no teaching of ranking therapists based on progress in therapy for an individual patient and for higher rated therapist responses as feedback to a therapist reply system Thus, the claims are free of the relevant prior art.
Response to Arguments
Applicant’s remarks filed April 6, 2026 have been fully considered, but they are not entirely persuasive. The following explains why:
Applicant’s additional arguments pertaining to the claim 1 rejected under 35 U.S.C. §103 are persuasive. A Second Nonfinal Office Action is sent with an updated rejection. Mutaro ‘083 teaches the limitations cited by the independent claims of ranking therapists and user responses. New references Olds and McNeil are relied on for providing samples of higher ranked replies and ranking therapists by diagnosis. The arguments pertaining to claims 8-10 are moot in light of the updated rejection and Office Action. The Primary reference is now changed (was not as related in the field of pertinent art as the new primary reference) and there is no impermissible hindsight reasoning for combining the three or four references, as a PHOSITA would be inclined to make the combinations.
Applicant’s arguments pertaining to subject matter eligibility are not persuasive. The claims have been addressed with regard to the updated 35 U.S.C. §101 rejection discussed above, and considered under relevant sections of the MPEP. The arguments at pages 6-8 of Applicant’s Remarks are not persuasive. At pages 6-8 the Examiner disagrees that there is not an abstract idea, that there is any practical application thereof or there is a technological improvement in the claims. The Examiner disagrees there is significantly more than the abstract idea. The Examiner disagrees at Pages 6-7 there is not an abstract idea. The current claims are included as a mental process(es) for the judicial exception as well as organizing human activity. Here the patient and therapist messaging and reply system and various computing units and software act as a computer tool used to employ the abstract idea. That it may be tedious or laborious to perform analyses in the mind or manually is not of consequence in the eligibility analysis. A physician would use the claimed additional elements including messaging and reply systems, computer and database as insignificant extra-solution activity to perform the abstract idea of organizing human activity or mental process, as discussed.
In addition, the Examiner respectfully disagrees at Pages. 7-8 that the claims recite an exception that is integrated into a practical application. The nominal recitation of the additional elements of a generic computer system, a patient messaging system, a therapist reply system and database are not sufficient to integrate the abstract idea into a practical application. These computer components are recited at a high level, and amount to applying the exception using a generic computer (See e.g. Updated PEG Example 47, claim 2, where the “detecting” and “analyzing” were mental processes, and “using the trained ANN” (similar to software executing on a computer for analyzing message history and determining progression over time) amounted to generic computer implementation). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. For at least these reasons and those stated above, the claims are not patent eligible. The Examiner disagrees at Pages 7-8 that there is a technological improvement in the claim limitations for creating a “learning loop” as described in the specification. Even if a learning loop as such were being explicitly claimed, it would amount to a generic computer implementation, discussed above. The Examiner also disagrees at Pages 8-9 that there is significantly more than the abstract idea. The additional elements amount to mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. For at least these reasons and those stated above, the amended claims are not patent eligible.
Conclusion
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/WILLIAM T. MONTICELLO/Examiner, Art Unit 3682
/FONYA M LONG/Supervisory Patent Examiner, Art Unit 3682
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