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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114 ("RCE"), including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on September 19, 2025, has been entered.
Status of Claims
Claims 1 and 4-22 were previously pending and subject to a Final Office Action having a notification date of March 28, 2025 (“Final Office Action”). Following the Final Office Action, Applicant filed the RCE and an amendment on September 19, 2025 (“Amendment”), amending claims 1, 10, and 21.
While Applicant indicates on page 10 of the Amendment that "claim 22 is presently cancelled," the status indicator for claim 22 reads "PREVIOUSLY PRESENTED." Therefore, the Examiner will assume claim 22 is still pending and not canceled.
The present non-final Office Action addresses pending claims 1 and 4-22 in the Amendment.
Response to Arguments
Response to Applicant’s Arguments Regarding Claim Rejections Under 35 USC §101
On page 10 of the Amendment, Applicant takes the position that the present claims recite “significantly more” than any abstract idea because they recite a particular manner of training, using, and updating “an escalation detection subsystem comprising a machine learning model and a rule-based model comprising a heuristics-based natural language processing (NLP) model” (e.g., via extracting temporal parameter features from data inputs and adjusting score weights "for training of the ML model" of the escalation detection subsystem).
However, a medical professional could readily "downweight" scores based on a temporal parameter (e.g., age) of the keywords, such as downweighting a first score if a time period of the temporal parameter deviates from present time by more than a threshold and downweighting a second score by a scaling factor corresponding to a duration of time of the temporal parameter. In this regard, that such weighting/downweighting of scores based on the temporal parameter is "for training of the machine learning model" just amounts to reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished which is equivalent to the words “apply it” (see MPEP § 2106.05(f)) and only serve to limit the “training” to the use of downweighted scores in the manner recited in the claims which merely “link[] the use of a judicial exception to a particular technological environment or field of use.” MPEP § 2106.05(h).
Claims that do no more than apply established methods of machine learning to a new data environment are not patent eligible. Recentive Analytics, Inc. v. Fox Corp., Fox Broadcasting Company, LLC, Fox Sports Productions, LLC, Case No. 23-2437, (Fed. Cir. 2025), pp. 10, 14. An abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment. Id. Requirements that the machine learning model be “iteratively trained” or dynamically adjusted do not represent a technological improvement because iterative training using selected training material and dynamic adjustments based on real-time changes are incident to the very nature of machine learning. Id., p. 12.
On page 11, Applicant asserts that the amendments to the claims further provide features to "effect a particular treatment for a disease or medication condition (e.g., suicidal ideation, as in claims 10 and 21)." However, there is no indication that initiating a call to a suicide hotline for the member actually treats the member experiencing the suicidal ideation in the first place. For instance, MPEP 2106.04(d)(2) discusses various examples of patent-eligible effecting of a particular treatment/prophylaxis for a disease/medical condition such as administering a lower than normal dosage of a beta blocker medication to a patient identified as having a poor metabolizer genotype, treating a patient having a blood glucose level over 250 mg/dl with insulin, and vaccinating a second group of cats in accordance with a lowest risk vaccination schedule. In contrast, merely initiating a call to a suicide hotline does not require that any sort of particular treatment (e.g., psychotherapy, etc.) is actually administered to the member/participant in manner that amounts to a particular treatment/prophylaxis.
The 35 USC 101 rejection is maintained.
Response to Applicant’s Arguments Regarding Claim Rejections Under 35 USC §103
These rejections are withdrawn in view of the Amendment.
Claim Objections
Claims 10 and 21 are objected to because of the following informalities:
In claim 10, the second to last line, it appears that "participant" should be changed to --member--.
In claim 21, line 3, it appears that "participant" should be changed to --member--.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1 and 4-22 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Each of independent claims 1 and 10 has been amended to recite determining a temporal parameter from the set of keywords and weighting the scores "for training of the machine learning model" using the temporal parameter as an input of the set of inputs, including downweighting a first score when a time period of the temporal parameter deviates from the present time by more than a threshold, and downweighting a second score by a scaling factor corresponding to a duration of time of the temporal parameter.
While [0104] of the present application generally discusses how the scores can be "[downweighted] if the associated time period deviates from present time by more than a predetermined threshold, [downweighted] according to a scaling factor corresponding to the duration of time," there is no indication that such downweighting is "for training of the machine learning model" as now recited in independent claims 1 and 10. In contrast, it appears that such disclosure regarding downweighting is a process that can be performed by a trained model/algorithm ([0106]) but not that such downweighting is used to perform training of a model.
The remaining claims are rejected based on their dependence from claims 1 or 10.
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 and 4-22 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.
Claim 1 recites the limitations "the message" and "the set of inputs" in line 13. There is insufficient antecedent basis for this limitation in the claim.
Claim 10 recites the limitations "the message" and "the set of inputs" in line 11. There is insufficient antecedent basis for this limitation in the claim.
The remaining claims are rejected based on their dependence from claims 1 or 10.
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.
Claim 1 and 4-22 are rejected under 35 U.S.C. §101 because the claimed invention is directed to an abstract idea without significantly more.
Subject Matter Eligibility Criteria - Step 1:
As claims 1 and 4-22 are directed to a method (i.e., a process), the claims are all within one of the four statutory categories. 35 USC §101.
Subject Matter Eligibility Criteria - Alice/Mayo Test: Step 2A - Prong One:
Regarding Prong One of Step 2A of the Alice/Mayo test (which collectively includes the guidance in the January 7, 2019 Federal Register notice and the October 2019 update issued by the USPTO as now incorporated into the MPEP, as supported by relevant case law), the claim limitations are to be analyzed to determine whether, under their broadest reasonable interpretation, they “recite” a judicial exception or in other words whether a judicial exception is “set forth” or “described” in the claims. MPEP 2106.04(II)(A)(1). An “abstract idea” judicial exception is subject matter that falls within at least one of the following groupings: a) certain methods of organizing human activity, b) mental processes, and/or c) mathematical concepts. MPEP 2106.04(a).
Representative independent claim 1 includes limitations that recite at least one abstract idea. Specifically, independent claim 1 recites:
A method for computer-aided escalation of a member in a digital platform, the method comprising:
training an escalation detection subsystem comprising a machine learning model and a rule-based model comprising a heuristics-based natural language processing (NLP) model, to predict a score associated with a clinical care escalation outcome, wherein training comprises training with labeled data comprising portions of chat transcripts between a participant and a coach in which the participant provides information informative of escalation to clinical care;
processing the message and the set of inputs with the trained escalation detection subsystem and using a set of prioritization parameters for the trained escalation detection subsystem to produce a predicted score for the member, the predicted score corresponding to a clinical care escalation outcome recommendation for the member, wherein processing the message comprises assigning, using the escalation detection subsystem, a set of scores to the message based upon a set of contexts determined from a set of keywords derived from the message,
wherein assigning the set of scores based upon the set of contexts comprises determining a temporal parameter from the set of keywords and weighting the set of scores for training of the machine learning model using the temporal parameter as an input of the set of inputs,
wherein weighting the set of scores comprises downweighting a first score of the set of scores if a time period of the temporal parameter deviates from present time by more than a threshold, and downweighting a second score of the set of scores by a scaling factor corresponding to a duration of time of the temporal parameter, and
wherein the predicted score is generated from the set of scores and corresponds to a care escalation outcome recommendation for the member;
retrieving a historical score associated with a historical message from the member;
aggregating the predicted score with the historical score to produce an aggregated score;
evaluating a set of satisfaction criteria based on the aggregated score, wherein:
in an event that the set of satisfaction criteria are satisfied, automatically triggering an adjustment in a care plan at the digital platform; and
preventing repetition of the adjustment in the care plan upon detecting prior triggering of the adjustment in the care plan for the member, wherein the adjustment comprises a change in features of the digital platform that are available to the member.
The Examiner submits that the foregoing underlined limitations constitute “mental processes” because they are observations/evaluations/judgments/analyses that can, at the currently claimed high level of generality, be practically performed in the human mind (e.g., with pen and paper). As an example, a medical professional/clinician could readily analyze the sentiment of keywords/text in messages from a member/patient to assign a set of “scores” to the message based on contexts of the wording/text. For instance, the medical professional could readily assign higher scores to keywords/phrases such as “major pain,” “emergency,” “stroke,” and lower scores to keywords/phrases such as “resolved,” “feeling healthy,” etc. Furthermore, the medical professional could readily "downweight" scores based on a temporal parameter (e.g., age) of the keywords, such as downweighting a first score if a time period of the temporal parameter deviates from present time by more than a threshold and downweighting a second score by a scaling factor corresponding to a duration of time of the temporal parameter.
Thereafter, the medical professional could determine a predicted score for the message from the set of scores indicative of a relative level of danger of the member in relation to a medical condition that corresponds to a “care escalation outcome recommendation” for the member/patient (e.g., via adding up the set of scores), aggregate the scores over time, trigger an adjustment in a care plan for the member (e.g., a change in features available to the patient/member, such as further monitoring, reduced communications, etc.) when the aggregated score exceeds a threshold (when “satisfaction criteria” are satisfied), and prevent repetition of the adjustment in the care plan upon detecting prior triggering of the adjustment in the care plan for the member (e.g., not repeatedly adjusting the care plan until a previous adjustment has completed).
Furthermore, in relation to predicting from the temporal parameter of the message that the participant/member is experiencing suicidal ideation (from independent claim 10), this step constitutes “mental processes” because it is an evaluation/judgment that can, at the currently claimed high level of generality, be practically performed in the human mind.
These recitations, under their broadest reasonable interpretation, are similar to the concepts of collecting information, analyzing it and displaying certain results of the collection and analysis in Electric Power Group, LLC, v. Alstom (830 F.3d 1350, 119 USPQe2d 1739 (Fed. Cir. 2016)). MPEP 2106.04(a)(2)(III).
In relation to automatically initiating a call to a suicide hotline for the member based on the suicidal ideation prediction (from independent claim 10), the Examiner submits that this limitation constitutes “certain methods of organizing human activity” because it relates to managing personal behavior or relationships or interactions between people (e.g., social activities, teaching, and following rules or instructions). That is, automatically initiating such a call relates to facilitating interactions between the member/participant experiencing suicidal ideation and a healthcare worker trained to manage such situations.
Accordingly, the claim recites at least one abstract idea.
Furthermore, dependent claims 4, 5, 7, 12-15, 18, 21, and 22 further define the at least one abstract idea (and thus fail to make the abstract idea any less abstract) as set forth below:
-Claims 4 and 18 call for preventing care plan adjustment when the satisfaction criteria is not met which can be practically performed in the human mind with pen and paper (“mental processes”). Furthermore, claim 18 calls for evaluating a set of satisfaction criteria based on the aggregated score which is practically performable in the human mind with pen and paper (“mental processes”)
-Claims 5 and 15 call for performing a (feature weighting) adjustment of the message using the prioritization parameters which can be practically performed in the human mind with pen and paper (“mental processes”). For instance, a clinician could assign higher weights to certain words and lower weights to other less important words.
-Claim 7 recites how the predicted score is determined based at least in part on the set of contexts (e.g., relative importance of certain words to certain medical conditions) associated with the message which can be practically performed in the human mind with pen and paper (“mental processes”).
-Claim 12 calls for performing a generic “adjustment” of the message (e.g., determining different treatment recommendations to be presented to a user) and determining a set of contexts associated with the adjusted message which again can be practically performed in the human mind with pen and paper (“mental processes”).
-Claim 13 calls for determining contexts associated with the message and predicting the score based on the contexts which can be practically performed in the human mind with pen and paper (“mental processes”).
-Claim 14 recites how the contexts are associated with an adjustment of the message which can be practically performed in the human mind with pen and paper (“mental processes”).
-Claim 21 calls for predicting from the temporal parameter of the message that the participant/member is experiencing suicidal ideation which constitutes “mental processes” because it is an evaluation/judgment that can, at the currently claimed high level of generality, be practically performed in the human mind. Claim 21 also calls for automatically initiating a call to a suicide hotline for the member based on the suicidal ideation prediction which constitutes “certain methods of organizing human activity” because it relates to managing personal behavior or relationships or interactions between people (e.g., social activities, teaching, and following rules or instructions). That is, automatically initiating such a call relates to facilitating interactions between the member/participant experiencing suicidal ideation and a healthcare worker trained to manage such situations.
-Claim 22 calls for determining the set of contexts upon performing a negation detection analysis configured to determine if a keyword of the set of keywords (including e.g., “depressed,” “blue,” “moody,” etc.) is positively recited which can be practically performed in the human mind with pen and paper (“mental processes”).
Subject Matter Eligibility Criteria - Alice/Mayo Test: Step 2A - Prong Two:
Regarding Prong Two of Step 2A of the Alice/Mayo test, it must be determined whether the claim as a whole integrates the abstract idea into a practical application. As noted at MPEP §2106.04(II)(A)(2), it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.” MPEP §2106.05(I)(A).
In the present case, the additional limitations beyond the above-noted at least one abstract idea recited in the claim are as follows (where the bolded portions are the “additional limitations” while the underlined portions continue to represent the at least one “abstract idea”):
A method for computer-aided (using computers or machinery as mere tools to perform the abstract idea as noted below, see MPEP § 2106.05(f)) escalation of a member in a digital platform (using computers or machinery as mere tools to perform the abstract idea as noted below, see MPEP § 2106.05(f)), the method comprising:
training an escalation detection subsystem comprising a machine learning model and a rule-based model comprising a heuristics-based natural language processing (NLP) model (merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished, see MPEP § 2106.05(f)), to predict a score associated with a clinical care escalation outcome, wherein training comprises training with labeled data comprising portions of chat transcripts between a participant and a coach in which the participant provides information informative of escalation to clinical care (merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished, see MPEP § 2106.05(f); mere field of use limitation as noted below, see MPEP § 2106.05(h));
processing the message and the set of inputs with the trained escalation detection subsystem and using a set of prioritization parameters for the trained escalation detection subsystem (merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished, see MPEP § 2106.05(f)) to produce a predicted score for the member, the predicted score corresponding to a clinical care escalation outcome recommendation for the member, wherein processing the message comprises assigning, using the escalation detection subsystem (merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished, see MPEP § 2106.05(f)), a set of scores to the message based upon a set of contexts determined from a set of keywords derived from the message,
wherein assigning the set of scores based upon the set of contexts comprises determining a temporal parameter from the set of keywords and weighting the set of scores for training of the machine learning model (merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished, see MPEP § 2106.05(f)) using the temporal parameter as an input of the set of inputs,
wherein weighting the set of scores comprises downweighting a first score of the set of scores if a time period of the temporal parameter deviates from present time by more than a threshold, and downweighting a second score of the set of scores by a scaling factor corresponding to a duration of time of the temporal parameter, and
wherein the predicted score is generated from the set of scores and corresponds to a care escalation outcome recommendation for the member;
retrieving a historical score associated with a historical message from the member (extra-solution activity as noted below (data gathering), see MPEP § 2106.05(g));
aggregating the predicted score with the historical score to produce an aggregated score;
evaluating a set of satisfaction criteria based on the aggregated score, wherein:
in an event that the set of satisfaction criteria are satisfied, automatically triggering an adjustment in a care plan at the digital platform (using computers or machinery as mere tools to perform the abstract idea as noted below, see MPEP § 2106.05(f)); and
preventing repetition of the adjustment in the care plan upon detecting prior triggering of the adjustment in the care plan for the member, wherein the adjustment comprises a change in features of the digital platform that are available to the member.
For the following reasons, the Examiner submits that the above identified additional limitations, when considered as a whole with the limitations reciting the at least one abstract idea, do not integrate the above-noted at least one abstract idea into a practical application.
Regarding the additional limitations of the method being computer-aided, the digital platform, and the escalation detection subsystem, the Examiner submits that these limitations amount to merely using a computer or other machinery as tools performing their typical functionality in conjunction with performing the above-noted at least one abstract idea (see MPEP § 2106.05(f)). For instance, to the extent that the mentally-performable care plan adjustment trigger is performed at or by the generically-recited “digital platform,” the Examiner asserts that doing so just amounts to merely using a computer or other machinery as tools performing their typical functionality in conjunction with performing the above-noted at least one abstract idea (“apply it”) (see MPEP § 2106.05(f)).
Regarding the additional limitations of receiving a historical score, the Examiner submits that this additional limitation merely adds insignificant extra-solution activity (data gathering; selecting data to be manipulated) to the at least one abstract idea in a manner that does not meaningfully limit the at least one abstract idea (see MPEP § 2106.05(g)).
Regarding the additional limitations of training the escalation detection subsystem including an ML model (set of NNs in the case of independent claim 10) and a rule/heuristics-based NLP model with labeled data comprising portions of chat transcripts between a participant and a coach in which the participant provides information informative of escalation to clinical care, and then using the trained escalation detection subsystem and set of prioritization parameters to process the message and inputs to produce the predicted score, the Examiner asserts that these additional limitations merely amount to reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished which is equivalent to the words “apply it” (see MPEP § 2106.05(f)).
Furthermore, that the weighting/downweighting of scores based on the temporal parameter is "for training of the machine learning model" also just amounts to reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished which is equivalent to the words “apply it” (see MPEP § 2106.05(f)).
Still further, these steps do not require any particular type of training methodology—they only serve to limit the “training” to the use of labeled chat transcripts between a participant and a coach in which the participant provides information informative of escalation to clinical care and thus merely “link[] the use of a judicial exception to a particular technological environment or field of use.” MPEP § 2106.05(h). Still further, the claims do not recite any details regarding how the escalation detection subsystem actually assigns the scores to generate the predicted score.
With reference to Applicant’s specification, [0042]-[0046] provide a generic discussion of rule-based models (e.g., heuristics-based models or other suitable algorithms) and ML models (e.g., deep learning models, NNs, etc. trained via supervised learning, unsupervised learning, etc.) for use in determining that a participant’s level of care should be adjusted. However, [0020]-[0028] and [0051] of the specification generally discuss how the escalation detection subsystem serves to automate the process of monitoring participants for escalation (which would normally be performed by a medical professional) rather than improving any underlying technologies for doing so.
Claims that do no more than apply established methods of machine learning to a new data environment are not patent eligible. Recentive Analytics, Inc. v. Fox Corp., Fox Broadcasting Company, LLC, Fox Sports Productions, LLC, Case No. 23-2437, (Fed. Cir. 2025), pp. 10, 14. An abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment. Id. Requirements that the machine learning model be “iteratively trained” or dynamically adjusted do not represent a technological improvement because iterative training using selected training material and dynamic adjustments based on real-time changes are incident to the very nature of machine learning. Id., p. 12.
Thus, taken alone, the additional elements do not integrate the at least one abstract idea into a practical application. Furthermore, looking at the additional limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. MPEP §2106.05(I)(A) and §2106.04(II)(A)(2).
For these reasons, representative independent claim 1 and analogous independent claim 10 do not recite additional elements that integrate the judicial exception into a practical application. Accordingly, representative independent claim 1 and analogous independent claim 10 are directed to at least one abstract idea.
The remaining dependent claim limitations not addressed above fail to integrate the abstract idea into a practical application as set forth below:
-Claims 2 and 17 recite how the escalation detection subsystem uses labeled data including a training message labeled with the clinical care escalation outcome which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)). For instance, as the escalation detection subsystem is configured to receive messages and output clinical care escalation outcome recommendations, then merely reciting how the subsystem uses labeled data including a training message labeled with the clinical care escalation outcome merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished.
-Claim 6 generically recites how the trained escalation detection subsystem includes a combination of a rule-based model and a set of trained NNs which amounts to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished which is equivalent to the words “apply it” (see MPEP § 2106.05(f)). For instance, what steps does the set of trained NNs perform that amount to the generic “feature weighting adjustment” of the message?
-Claim 7 recites how it is the “rule-based model” that determines the set of contexts which amounts to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished which is equivalent to the words “apply it” (see MPEP § 2106.05(f)). For instance, what steps does the rule-based model perform to determine the set of contexts?
-Claims 8 and 19 recite updating the escalation detection subsystem in response to automatically triggering the adjustment which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)). For instance, how is the escalation detection subsystem updated?
-Claims 9 and 20 recite how the updating includes retraining the escalation detection subsystem based on the message, the aggregated score, and the adjustment in the care plan which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)). For instance, how are the message, the aggregated score, and the adjustment in the care plan used to retrain the system?
-Claim 11 recites how the NN set includes multiple NNs which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)).
-Claim 12 recites how the first NN performs the message adjustment, the rule-based model determines the set of contexts, and the second NN determines the aggregated score which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)). For instance, what steps does the first NN perform that amount to the adjustment of the message, what steps does the rule-based model perform to determine the set of contexts, and what steps does the second NN perform to determine the aggregated score?
-Claim 13 recites how the set of contexts are determined by the rule-based model which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)).
-Claim 14 recites how the message adjustment is performed by the NN set which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)).
-Claim 15 recites how the learned set of prioritization parameters is learned during training of the escalation detection subsystem which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)).
-Claim 16 recites how the triggering of the care plan adjustment includes adjusting an member user device interface which amounts to merely using a computer or other machinery as tools performing their typical functionality in conjunction with performing the above-noted at least one abstract idea (see MPEP § 2106.05(f)).
When the above additional limitations are considered as a whole along with the limitations directed to the at least one abstract idea, the at least one abstract idea is not integrated into a practical application. Therefore, the claims are directed to at least one abstract idea.
Subject Matter Eligibility Criteria - Alice/Mayo Test: Step 2B:
Regarding Step 2B of the Alice/Mayo test, independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for reasons the same as those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application.
Regarding the additional limitations of the method being computer-aided, the digital platform, and the escalation detection subsystem, the Examiner submits that these limitations amount to merely using a computer or other machinery as tools performing their typical functionality in conjunction with performing the above-noted at least one abstract idea (see MPEP § 2106.05(f)). For instance, to the extent that the mentally-performable care plan adjustment trigger is performed at or by the generically-recited “digital platform,” the Examiner asserts that doing so just amounts to merely using a computer or other machinery as tools performing their typical functionality in conjunction with performing the above-noted at least one abstract idea (“apply it”) (see MPEP § 2106.05(f)).
Regarding the additional limitations of training the escalation detection subsystem including an ML model (set of NNs in the case of independent claim 10) and a rule/heuristics-based NLP model with labeled data comprising portions of chat transcripts between a participant and a coach in which the participant provides information informative of escalation to clinical care, and then using the trained escalation detection subsystem and set of prioritization parameters to process the message and inputs to produce the predicted score, the Examiner asserts that these additional limitations merely amount to reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished which is equivalent to the words “apply it” (see MPEP § 2106.05(f)).
Furthermore, that the weighting/downweighting of scores based on the temporal parameter is "for training of the machine learning model" also just amounts to reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished which is equivalent to the words “apply it” (see MPEP § 2106.05(f)).
Still further, these steps do not require any particular type of training methodology—they only serve to limit the “training” to the use of labeled chat transcripts between a participant and a coach in which the participant provides information informative of escalation to clinical care and thus merely “link[] the use of a judicial exception to a particular technological environment or field of use.” MPEP § 2106.05(h). Still further, the claims do not recite any details regarding how the escalation detection subsystem actually assigns the scores to generate the predicted score.
With reference to Applicant’s specification, [0042]-[0046] provide a generic discussion of rule-based models (e.g., heuristics-based models or other suitable algorithms) and ML models (e.g., deep learning models, NNs, etc. trained via supervised learning, unsupervised learning, etc.) for use in determining that a participant’s level of care should be adjusted. However, [0020]-[0028] and [0051] of the specification generally discuss how the escalation detection subsystem serves to automate the process of monitoring participants for escalation (which would normally be performed by a medical professional) rather than improving any underlying technologies for doing so.
Claims that do no more than apply established methods of machine learning to a new data environment are not patent eligible. Recentive Analytics, Inc. v. Fox Corp., Fox Broadcasting Company, LLC, Fox Sports Productions, LLC, Case No. 23-2437, (Fed. Cir. 2025), pp. 10, 14. An abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment. Id. Requirements that the machine learning model be “iteratively trained” or dynamically adjusted do not represent a technological improvement because iterative training using selected training material and dynamic adjustments based on real-time changes are incident to the very nature of machine learning. Id., p. 12.
Regarding the additional limitation directed to receiving a historical score which the Examiner submits merely add insignificant extra-solution activity to the abstract idea, the Examiner has reevaluated such limitation and determined it to not be unconventional as it merely consists of receiving/transmitting data over a network. See Intellectual Ventures I v. Symantec Corp., 838 F.3d 1307, 1321, 120 USPQ2d 1353, 1362 (Fed. Cir. 2016); See MPEP 2106.05(d)(II).
The dependent claims also do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the dependent claims do not integrate the at least one abstract idea into a practical application.
-Claims 2 and 17 recite how the escalation detection subsystem uses labeled data including a training message labeled with the clinical care escalation outcome which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)). For instance, as the escalation detection subsystem is configured to receive messages and output clinical care escalation outcome recommendations, then merely reciting how the subsystem uses labeled data including a training message labeled with the clinical care escalation outcome merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished.
-Claim 6 generically recites how the trained escalation detection subsystem includes a combination of a rule-based model and a set of trained NNs which amounts to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished which is equivalent to the words “apply it” (see MPEP § 2106.05(f)). For instance, what steps does the set of trained NNs perform that amount to the generic “feature weighting adjustment” of the message?
-Claim 7 recites how it is the “rule-based model” that determines the set of contexts which amounts to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished which is equivalent to the words “apply it” (see MPEP § 2106.05(f)). For instance, what steps does the rule-based model perform to determine the set of contexts?
-Claims 8 and 19 recite updating the escalation detection subsystem in response to automatically triggering the adjustment which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)). For instance, how is the escalation detection subsystem updated?
-Claims 9 and 20 recite how the updating includes retraining the escalation detection subsystem based on the message, the aggregated score, and the adjustment in the care plan which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)). For instance, how are the message, the aggregated score, and the adjustment in the care plan used to retrain the system?
-Claim 11 recites how the NN set includes multiple NNs which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)).
-Claim 12 recites how the first NN performs the message adjustment, the rule-based model determines the set of contexts, and the second NN determines the aggregated score which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)). For instance, what steps does the first NN perform that amount to the adjustment of the message, what steps does the rule-based model perform to determine the set of contexts, and what steps does the second NN perform to determine the aggregated score?
-Claim 13 recites how the set of contexts are determined by the rule-based model which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)).
-Claim 14 recites how the message adjustment is performed by the NN set which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)).
-Claim 15 recites how the learned set of prioritization parameters is learned during training of the escalation detection subsystem which merely recites the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)).
-Claim 16 recites how the triggering of the care plan adjustment includes adjusting an member user device interface which amounts to merely using a computer or other machinery as tools performing their typical functionality in conjunction with performing the above-noted at least one abstract idea (see MPEP § 2106.05(f)).
Therefore, claims 1 and 4-22 are ineligible under 35 USC §101.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. U.S. Patent App. Pub. No. 2016/0170961 and U.S. Patent Nos. 9,355,173 and 8,676,795 disclose systems that analyze and adjust significance weights of keywords based on age of the keywords.
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/JONATHON A. SZUMNY/Patent Examiner, Art Unit 3686