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 action is in reply to the claims filed on 03 July 2024. Claims 1-20 are currently pending and have been examined.
Claim Objections
Claim 13 is objected to because of the following informalities: “14ng” in line 10 appears to be a typographical error of “among.” Appropriate correction is required.
Claim 14 is objected to because of the following informalities: “14ng” in line 3 appears to be a typographical error of “among.” Appropriate correction is required.
Claim 19 is objected to because of the following informalities: “14ng” in line 101 appears to be a typographical error of “among.” Appropriate correction is required.
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 18-20 are rejected under 35 USC § 101
Step 1: Is the claim to a process, machine, manufacture, or composition or matter?
Claims 18-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claims do not fall within at least one of the four categories of patent eligible subject matter because claim 18-20 encompass a transitory medium given the claim's broadest reasonable interpretation in light of paragraph [0059] of the published specification. Such media have been held to be ineligible subject matter under 35 USC §101. See In re Nuijten, 500 F.3d 1346, 1356-57 (Fed. Cir. 2007). It is suggested that claim 1 be amended to recite a “non-transitory” computer readable medium to overcome this rejection.
Claims 1-20 are rejected under 35 USC § 101
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
Claims 1-20 fall within one or more statutory categories. Claims 1-14 fall within the category of a process. Claims 15-17 fall within the category of a manufacture. Claims 18-20, if amended to recite “non-transitory,” fall within the category of a manufacture.
Step 2A Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Claims 1-20 recite an abstract idea. Representative claim 1 recites:
accessing a first analytic method specifying questions to pose, possible answers to each question, and routing targets for each possible answer to each question, each routing target being another question or a recommended action;
performing the first analytic method for a particular patient, at a time when a spoken natural language conversation is occurring about the patient, to reach a point in the performance of the first analytic method where a first question is pending;
receiving a representation of a first portion of the spoken conversation, at a time contemporaneous with the occurrence of the first portion of the spoken conversation;
automatically attributing to the first portion of the spoken conversation a meaning predicted for the first portion of the spoken conversation;
using the predicted meaning to select one of the possible answers specified for the first question; and
proceeding in the performance of the first analytic method to the routing target specified for the selected possible answer.
Therefore, the claim as a whole is directed to “having a conversation,” which is an abstract idea because it is a method of organizing human activity. “Having a conversation” is considered to be a method of organizing human activity because it is an example of managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). This is an example of the interaction between two individuals discussing a patient.
Alternatively, the claims can be considered to be directed to a mental process because they recite concepts capable of being performed in the human mind (including an observation, evaluation, judgment, opinion).
Step 2A Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application?
This judicial exception is not integrated into a practical application. In particular, claim 1 recites the following additional element(s):
The method is in a “computing system.”
The additional elements individually or in combination do not integrate the exception into a practical application. The additional element merely recites the words ‘‘apply it’’ (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, 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. Claim 1 is directed to an abstract idea.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Claim 1 does not include additional elements, considered individually or in combination, 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 element(s), individually and in combination, merely recites the words ‘‘apply it’’ (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, claim 1 is ineligible.
Dependent claim 2 recites the method of claim 1, wherein:
the received representation is a textual transcript of the first portion of the spoken conversation,
or the received representation is an audio sequence reflecting the first portion of the spoken conversation, and the method further comprises applying a speech-to-text mechanism to the received representation in order to obtain a textual transcript of the first portion of the spoken conversation,
or the received representation is an audio/video sequence reflecting the first portion of the spoken conversation, and the method further comprises a speech-to-text mechanism to an audio channel of the received representation in order to obtain a textual transcript of the first portion of the spoken conversation.
The additional elements present in this claim merely recites the words ‘‘apply it’’ (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). These types of additional elements are not enough to integrate the abstract idea into a practical application, nor do they amount to significantly more than the judicial exception. Accordingly, claim 2 is ineligible.
Dependent claim 3 recites the method of claim 1, wherein:
the automatic attribution is performed using a large language model.
The additional elements present in this claim merely recites the words ‘‘apply it’’ (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). These types of additional elements are not enough to integrate the abstract idea into a practical application, nor do they amount to significantly more than the judicial exception. Accordingly, claim 3 is ineligible.
Dependent claim 4 recites the method of claim 1, wherein:
proceeding in the performance of the first analytic method comprises: where the routing target specified for the selected possible answer is an additional question of the first analytic method, displaying the additional question; and
where the routing target specified for the selected possible answer is a recommended action, displaying information about the recommended action.
This merely further limits the abstract idea of claim 1 discussed above and does not provide further additional elements. Therefore, claim 4 is considered to be ineligible.
Dependent claim 5 recites the method of claim 1, wherein:
displaying a visual indication that the selected possible answer was automatically selected.
This merely further limits the abstract idea of claim 1 discussed above and does not provide further additional elements. Therefore, claim 5 is considered to be ineligible.
Dependent claim 6 recites the method of claim 1, wherein:
receiving a representation of a second portion of the spoken conversation, at a time when a second question of the first analytic method is pending;
automatically attributing to the second portion of the spoken conversation a meaning predicted for the second portion of the spoken conversation;
using the predicted meaning to select one of the possible answers specified for a third question of the first analytic method that is downstream of the second question; and
pruning the first analytic method so that any routing targets that specify the third question instead specify the routing target for the possible answer selected for the third question.
This merely further limits the abstract idea of claim 1 discussed above and does not provide further additional elements. Therefore, claim 6 is considered to be ineligible.
Dependent claim 7 recites the method of claim 6, wherein:
displaying a visual indication that the possible answer selected for the third question was automatically selected.
This merely further limits the abstract idea of claim 6 discussed above and does not provide further additional elements. Therefore, claim 7 is considered to be ineligible.
Dependent claim 8 recites the method of claim 1, wherein:
displaying visual indications of possible recommended actions that narrow during performance of the first analytic method.
This merely further limits the abstract idea of claim 1 discussed above and does not provide further additional elements. Therefore, claim 8 is considered to be ineligible.
Dependent claim 9 recites the method of claim 1, wherein:
at a time when a second question of the first analytic method is pending, displaying the second question and its possible answers;
receiving input choosing one of the displayed possible answers; and
proceeding in the performance of the first analytic method to the routing target specified for the chosen possible answer.
This merely further limits the abstract idea of claim 1 discussed above and does not provide further additional elements. Therefore, claim 9 is considered to be ineligible.
Dependent claim 10 recites the method of claim 1, wherein:
receiving input disapproving the selection of the selected possible answer to the first question; and
in response to receiving the input, and the performance of the first analytic method, returning to the earlier state where the first question is pending.
This merely further limits the abstract idea of claim 1 discussed above and does not provide further additional elements. Therefore, claim 10 is considered to be ineligible.
Dependent claim 11 recites the method of claim 1, wherein:
the routing target specified for the selected possible answer is a recommended action, the method further comprising:
displaying an indication of the recommended action;
receiving input ratifying the recommended action; and
in response to receiving the input, sending an instruction to perform the recommended action on behalf of the patient.
This merely further limits the abstract idea of claim 1 discussed above and does not provide further additional elements. Therefore, claim 11 is considered to be ineligible.
Dependent claim 12 recites the method of claim 11, wherein:
the recommended action is a medical order or a referral.
This merely further limits the abstract idea of claim 11 discussed above and does not provide further additional elements. Therefore, claim 12 is considered to be ineligible.
Dependent claim 13 recites the method of claim 1, wherein:
accessing a plurality of analytic methods applicable to the patient that includes the first analytic method;
at a time before performance of the first analytic method, receiving a representation of a second portion of the spoken conversation that precedes the first portion of the spoken conversation;
automatically attributing to the second portion of the spoken conversation a meaning predicted for the second portion of the spoken conversation;
using the meaning predicted for the second portion of the spoken conversation to select the first analytic method from among the plurality of analytic methods for performance.
This merely further limits the abstract idea of claim 1 discussed above and does not provide further additional elements. Therefore, claim 13 is considered to be ineligible.
Dependent claim 14 recites the method of claim 1, wherein:
accessing trigger symptoms each associated with at least one analytic method among a plurality of analytic methods applicable to the patient that includes the first analytic method;
at a time before performance of the first analytic method, receiving a representation of a second portion of the spoken conversation that precedes the first portion of the spoken conversation;
automatically attributing to the second portion of the spoken conversation a meaning predicted for the second portion of the spoken conversation;
using the meaning predicted for the second portion of the spoken conversation to select one or more of the accessed trigger symptoms; and
displaying visual indications of the selected trigger symptoms.
This merely further limits the abstract idea of claim 1 discussed above and does not provide further additional elements. Therefore, claim 14 is considered to be ineligible.
Dependent claim 15 recites the one or more memories that store an analytic data structure reflecting a method that is substantially similar to of claim 1. This includes the recitation of:
One or more memories.
The additional elements present in this claim merely recites the words ‘‘apply it’’ (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). These types of additional elements are not enough to integrate the abstract idea into a practical application, nor do they amount to significantly more than the judicial exception. Accordingly, claim 15 is ineligible.
Dependent claim 16 recites the method of claim 15, wherein:
a second one of the one or more entries was added to the data structure in response to user input explicitly selecting the possible answer indicated by the second entry for the corresponding question.
The additional elements present in this claim merely recites the words ‘‘apply it’’ (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). These types of additional elements are not enough to integrate the abstract idea into a practical application, nor do they amount to significantly more than the judicial exception. Accordingly, claim 16 is ineligible.
Dependent claim 17 recites the method of claim 15, wherein:
a second one of the one or more entries was added to the data structure in response to automatic selection of the indicated possible answer for the corresponding question based upon application of a natural language understanding mechanism to a representation of a spoken conversation discussing the patient at a time before the first question was pending.
The additional elements present in this claim merely recites the words ‘‘apply it’’ (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). These types of additional elements are not enough to integrate the abstract idea into a practical application, nor do they amount to significantly more than the judicial exception. Accordingly, claim 17 is ineligible.
Claims 18-20 are parallel in nature to claims 1, 11 and 13. Accordingly claims 18-20 are rejected as being directed towards ineligible subject matter based upon the same analysis above.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Johnson et al. (U.S. 2023/0386620), hereinafter “Johnson,” in view of Gnanasambandam et al. (U.S. 2022/0384003), hereinafter “Gnanasambandam.”
Regarding Claim 1, Johnson discloses method in a computing system, comprising:
accessing a first analytic method specifying questions to pose, possible answers to each question (See Johnson Fig. 2 and [0030] system can use decision trees of questions connected to possible answers and final recommendations.), and routing targets for each possible answer to each question (See Johnson [0034] Based at least in part upon one or more answers to the first questions, one or more second questions can be determined and provided to the user. The user can be classified into one or more categories based at least in part upon answers provided to the first questions and the second questions. A recommendation for the user can be generated based at least in part upon the classification of the user. [0035] if the user provides a first answer to a first question, a first subset of second questions may follow. However, if the user provides a second answer, different from the first answer, a second subset of second questions may follow.), each routing target being another question or a recommended action (See Johnson [0017] may provide output such as a recommendation or summary as to whether the patient should seek genetic counseling, information regarding risk facts, classifications, groupings, educational information, and/or the like.);
performing the first analytic method for a particular patient, … to reach a point in the performance of the first analytic method where a first question is pending (See Johnson [0036] after a question is posed to the user, the user may provide an open-form answer, which may then be evaluated using one or more machine learning systems, such as a large language model, to extract salient information for processing. This answer is in response to a pending first question.);
receiving a representation of a first portion of the spoken conversation, at a time contemporaneous with the occurrence of the first portion of the spoken conversation (See Johnson [0036] after a question is posed to the user, the user may provide an open-form answer, which may then be evaluated using one or more machine learning systems, such as a large language model, to extract salient information for processing.);
automatically attributing to the first portion of the spoken conversation a meaning predicted for the first portion of the spoken conversation (See Johnson [0036] after a question is posed to the user, the user may provide an open-form answer, which may then be evaluated using one or more machine learning systems, such as a large language model, to extract salient information for processing.);
using the predicted meaning to select one of the possible answers specified for the first question (See Johnson [0036] the user may provide an open-form answer, which may then be evaluated using one or more machine learning systems, such as a large language model, to extract salient information for processing and determining the answer to the question.); and
proceeding in the performance of the first analytic method to the routing target specified for the selected possible answer (See Johnson [0035] for example, if the user provides a first answer to a first question, a first subset of second questions may follow. However, if the user provides a second answer, different from the first answer, a second subset of second questions may follow.).
Johnson does not disclose:
performing the first analytic method for a particular patient, at a time when a spoken natural language conversation is occurring about the patient.
Gnanasambandam teaches:
performing the first analytic method for a particular patient, at a time when a spoken natural language conversation is occurring about the patient (See Gnanasambandam [0175] the system receives text questions and answers via text input through a microphone (e.g., words spoken into the user device).).
The system of Gnanasambandam is applicable to the disclosure of Johnson as they both share characteristics and capabilities, namely, they are directed to processing patient related questions and answers. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Johnson to include elements as taught by Gnanasambandam. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Johnson in order to improve the health outcomes of a group by improving clinical outcomes while lowering costs (see Gnanasambandam [0002]).
Regarding claim 2, Johnson in view of Gnanasambandam discloses the method of claim 1 as discussed above. Johnson does not further disclose a method, wherein:
the received representation is a textual transcript of the first portion of the spoken conversation,
or the received representation is an audio sequence reflecting the first portion of the spoken conversation, and the method further comprises applying a speech-to-text mechanism to the received representation in order to obtain a textual transcript of the first portion of the spoken conversation,
or the received representation is an audio/video sequence reflecting the first portion of the spoken conversation, and the method further comprises a speech-to-text mechanism to an audio channel of the received representation in order to obtain a textual transcript of the first portion of the spoken conversation.
Gnanasambandam teaches:
the received representation is a textual transcript of the first portion of the spoken conversation (See Gnanasambandam [0175] the system receives text questions and answers via text input through a microphone (e.g., words spoken into the user device), and text typed on a keyboard or on a graphical user interface.),
or the received representation is an audio sequence reflecting the first portion of the spoken conversation, and the method further comprises applying a speech-to-text mechanism to the received representation in order to obtain a textual transcript of the first portion of the spoken conversation (See Gnanasambandam [0175] the system receives text questions and answers via text input through a microphone (e.g., words spoken into the user device), and text typed on a keyboard or on a graphical user interface.),
or the received representation is an audio/video sequence reflecting the first portion of the spoken conversation, and the method further comprises a speech-to-text mechanism to an audio channel of the received representation in order to obtain a textual transcript of the first portion of the spoken conversation (See Gnanasambandam [0175] the system receives text questions and answers via text input through a microphone (e.g., words spoken into the user device), and text typed on a keyboard or on a graphical user interface.).
The system of Gnanasambandam is applicable to the disclosure of Johnson as they both share characteristics and capabilities, namely, they are directed to processing patient related questions and answers. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Johnson to include elements as taught by Gnanasambandam. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Johnson in order to improve the health outcomes of a group by improving clinical outcomes while lowering costs (see Gnanasambandam [0002]).
Regarding claim 3, Johnson in view of Gnanasambandam discloses the method of claim 1 as discussed above. Johnson further discloses a method, wherein:
the automatic attribution is performed using a large language model (See Johnson [0036] the user may provide an open-form answer, which may then be evaluated using one or more machine learning systems, such as a large language model, to extract salient information for processing.).
Regarding claim 4, Johnson in view of Gnanasambandam discloses the method of claim 1 as discussed above. Johnson further discloses a method, wherein:
proceeding in the performance of the first analytic method comprises: where the routing target specified for the selected possible answer is an additional question of the first analytic method, displaying the additional question (See Johnson [0035] for example, if the user provides a first answer to a first question, a first subset of second questions may follow. However, if the user provides a second answer, different from the first answer, a second subset of second questions may follow.); and
where the routing target specified for the selected possible answer is a recommended action, displaying information about the recommended action (See Johnson [0017] may provide output such as a recommendation or summary as to whether the patient should seek genetic counseling, information regarding risk facts, classifications, groupings, educational information, and/or the like.).
Regarding claim 5, Johnson in view of Gnanasambandam discloses the method of claim 1 as discussed above. Johnson does not further disclose a method, wherein:
displaying a visual indication that the selected possible answer was automatically selected.
Gnanasambandam teaches:
displaying a visual indication that the selected possible answer was automatically selected (See Gnanasambandam Fig. 47 and [0484] system includes a visual indication that some of the form was filled out automatically based on past information (“We were able to obtain most of your medical history information from another form you completed in the past…”).).
The system of Gnanasambandam is applicable to the disclosure of Johnson as they both share characteristics and capabilities, namely, they are directed to processing patient related questions and answers. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Johnson to include elements as taught by Gnanasambandam. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Johnson in order to improve the health outcomes of a group by improving clinical outcomes while lowering costs (see Gnanasambandam [0002]).
Regarding claim 6, Johnson further discloses a method, wherein:
receiving a representation of a second portion of the … conversation, at a time when a second question of the first analytic method is pending (See Johnson [0036] after a question is posed to the user, the user may provide an open-form answer, which may then be evaluated using one or more machine learning systems, such as a large language model, to extract salient information for processing. This answer is in response to a pending question.);
automatically attributing to the second portion of the spoken conversation a meaning predicted for the second portion of the spoken conversation 9See Johnson [0036] after a question is posed to the user, the user may provide an open-form answer, which may then be evaluated using one or more machine learning systems, such as a large language model, to extract salient information for processing.);
using the predicted meaning to select one of the possible answers specified for a third question of the first analytic method that is downstream of the second question (See Johnson [0036] after a question is posed to the user, the user may provide an open-form answer, which may then be evaluated using one or more machine learning systems, such as a large language model, to extract salient information for processing. [0018] based on input responses provided by the user, may add or remove downstream questions, thereby streamlining the approach for the user.); and
pruning the first analytic method so that any routing targets that specify the third question instead specify the routing target for the possible answer selected for the third question (See Johnson [0018] based on input responses provided by the user, may add or remove downstream questions, thereby streamlining the approach for the user.).
Johnson does not disclose:
the conversation is a spoken conversation.
Gnanasambandam teaches:
the conversation is a spoken conversation (See Gnanasambandam [0175] the system receives text questions and answers via text input through a microphone (e.g., words spoken into the user device).).
The system of Gnanasambandam is applicable to the disclosure of Johnson as they both share characteristics and capabilities, namely, they are directed to processing patient related questions and answers. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Johnson to include elements as taught by Gnanasambandam. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Johnson in order to improve the health outcomes of a group by improving clinical outcomes while lowering costs (see Gnanasambandam [0002]).
Regarding claim 7, Johnson in view of Gnanasambandam discloses the method of claim 6 as discussed above. Johnson does not further disclose a method, wherein:
displaying a visual indication that the possible answer selected for the third question was automatically selected.
Gnanasambandam teaches:
displaying a visual indication that the possible answer selected for the third question was automatically selected (See Gnanasambandam Fig. 47 and [0484] system includes a visual indication that some of the form was filled out automatically based on past information (“We were able to obtain most of your medical history information from another form you completed in the past…”).).
The system of Gnanasambandam is applicable to the disclosure of Johnson as they both share characteristics and capabilities, namely, they are directed to processing patient related questions and answers. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Johnson to include elements as taught by Gnanasambandam. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Johnson in order to improve the health outcomes of a group by improving clinical outcomes while lowering costs (see Gnanasambandam [0002]).
Regarding claim 8, Johnson in view of Gnanasambandam discloses the method of claim 1 as discussed above. Johnson further discloses a method, wherein:
displaying visual indications of possible recommended actions that narrow during performance of the first analytic method (See Johnson [0024] the system can provide a copy of the results in a comprehensive report. Such a report may include individual responses by the patient, along with a summary indicating whether a user should seek genetic testing for a potential medical condition. This final summary shows a narrowing of recommendations (seek counseling or don’t seek counseling).).
Regarding claim 9, Johnson in view of Gnanasambandam discloses the method of claim 1 as discussed above. Johnson further discloses a method, wherein:
at a time when a second question of the first analytic method is pending, displaying the second question and its possible answers (See Fig. 1B and Johnson [0036] questions may be presented to the user in the form of a limited set of responses that correspond to an input. For example, a first question may include a list of potential answers and a user input may correspond to selection of one or more of the potential answers.);
receiving input choosing one of the displayed possible answers (See Fig. 1B and Johnson [0036] questions may be presented to the user in the form of a limited set of responses that correspond to an input. For example, a first question may include a list of potential answers and a user input may correspond to selection of one or more of the potential answers.); and
proceeding in the performance of the first analytic method to the routing target specified for the chosen possible answer (See Johnson [0035] for example, if the user provides a first answer to a first question, a first subset of second questions may follow. However, if the user provides a second answer, different from the first answer, a second subset of second questions may follow.).
Regarding claim 10, Johnson in view of Gnanasambandam discloses the method of claim 1 as discussed above. Johnson does not further disclose a method, wherein:
receiving input disapproving the selection of the selected possible answer to the first question; and
in response to receiving the input, and the performance of the first analytic method, returning to the earlier state where the first question is pending.
Gnanasambandam teaches:
receiving input disapproving the selection of the selected possible answer to the first question (See Gnanasambandam [0383] The physician may be presented with options to verify the accuracy of portions or all of the cognified data for the particular patient. For example, the physician may select a first graphical element (e.g., button, checkbox, etc.) next to portions of the cognified data that are accurate and may select a second graphical element next to portions of the cognified data that are inaccurate.); and
in response to receiving the input, and the performance of the first analytic method, returning to the earlier state where the first question is pending (See Gnanasambandam [0383] if the data is indicated as being inaccurate, an input box may appear and a notification may be presented to provide a reason why the portion is inaccurate and to provide corrected information. This is an example of returning to an earlier state, so that the information can be updated.).
The system of Gnanasambandam is applicable to the disclosure of Johnson as they both share characteristics and capabilities, namely, they are directed to processing patient related questions and answers. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Johnson to include elements as taught by Gnanasambandam. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Johnson in order to improve the health outcomes of a group by improving clinical outcomes while lowering costs (see Gnanasambandam [0002]).
Regarding claim 11, Johnson in view of Gnanasambandam discloses the method of claim 1 as discussed above. Johnson further discloses a method, wherein:
the routing target specified for the selected possible answer is a recommended action (See Johnson Fig. 1C and [0024] the system can take the results of the questions and recommend the user schedule an appointment.), the method further comprising:
displaying an indication of the recommended action (See Johnson Fig. 1C and [0024] the system can take the results of the questions and recommend the user schedule an appointment.);
receiving input ratifying the recommended action (See Johnson Fig. 1C and [0024] the system can take the results of the questions and they may be provided the option of scheduling an appointment through the user interface. This is a ratification of the recommended action.); and
in response to receiving the input, sending an instruction to perform the recommended action on behalf of the patient (See Johnson Fig. 1C and [0024] the system can take the results of the questions and they may be provided the option of scheduling an appointment through the user interface. This user interface element is understood to initiate the performance of the recommended scheduling of an appointment.).
Regarding claim 12, Johnson in view of Gnanasambandam discloses the method of claim 11 as discussed above. Johnson further discloses a method, wherein:
the recommended action is a medical order or a referral (See Johnson Fig. 1C and [0024] the system can take the results of the questions and they may be provided the option of scheduling an appointment with a specialist. This meets the broadest reasonable interpretation of a “referral.”).
Regarding claim 13, Johnson in view of Gnanasambandam discloses the method of claim 1 as discussed above. Johnson further discloses a method, wherein:
accessing a plurality of analytic methods applicable to the patient that includes the first analytic method (See Johnson Fig. 2 and [0030] system can use decision trees of questions connected to possible answers and final recommendations.);
at a time before performance of the first analytic method, receiving a representation of a second portion of the spoken conversation that precedes the first portion of the spoken conversation (See Johnson [0036] after a question is posed to the user, the user may provide an open-form answer, which may then be evaluated using one or more machine learning systems, such as a large language model, to extract salient information for processing.);
automatically attributing to the second portion of the spoken conversation a meaning predicted for the second portion of the spoken conversation (See Johnson [0034] Based at least in part upon one or more answers to the first questions, one or more second questions can be determined and provided to the user. The user can be classified into one or more categories based at least in part upon answers provided to the first questions and the second questions. A recommendation for the user can be generated based at least in part upon the classification of the user.);
using the meaning predicted for the second portion of the spoken conversation to select the first analytic method from among the plurality of analytic methods for performance (See Johnson [0034] Based at least in part upon one or more answers to the first questions, one or more second questions can be determined and provided to the user. The user can be classified into one or more categories based at least in part upon answers provided to the first questions and the second questions. A recommendation for the user can be generated based at least in part upon the classification of the user. See Fig. 2 and [0030] system can use decision trees of questions connected to possible answers and final recommendations.).
Regarding claim 14, Johnson in view of Gnanasambandam discloses the method of claim 1 as discussed above. Johnson further discloses a method, wherein:
at a time before performance of the first analytic method, receiving a representation of a second portion of the spoken conversation that precedes the first portion of the spoken conversation (See Johnson [0036] after a question is posed to the user, the user may provide an open-form answer, which may then be evaluated using one or more machine learning systems, such as a large language model, to extract salient information for processing.);
automatically attributing to the second portion of the spoken conversation a meaning predicted for the second portion of the spoken conversation (See Johnson [0034] Based at least in part upon one or more answers to the first questions, one or more second questions can be determined and provided to the user. The user can be classified into one or more categories based at least in part upon answers provided to the first questions and the second questions. A recommendation for the user can be generated based at least in part upon the classification of the user.);
using the meaning predicted for the second portion of the spoken conversation to select one or more of the accessed trigger symptoms (See Johnson [0034] Based at least in part upon one or more answers to the first questions, one or more second questions can be determined and provided to the user. The user can be classified into one or more categories based at least in part upon answers provided to the first questions and the second questions. A recommendation for the user can be generated based at least in part upon the classification of the user. See Fig. 2 and [0030] system can use decision trees of questions connected to possible answers and final recommendations.).
Johnson does not disclose:
accessing trigger symptoms each associated with at least one analytic method among a plurality of analytic methods applicable to the patient that includes the first analytic method;
displaying visual indications of the selected trigger symptoms.
Gnanasambandam teaches:
accessing trigger symptoms each associated with at least one analytic method among a plurality of analytic methods applicable to the patient that includes the first analytic method (See Gnanasambandam [0115] the system uses knowledge graphs that connect various symptoms with potential conditions/diseases. [0116] if a person exhibits certain symptoms and has certain laboratory tests performed, then that person may have a certain medical condition (e.g., type 2 diabetes mellitus) that is identified in the knowledge graphs using the logical structures. See also [0266].);
displaying visual indications of the selected trigger symptoms (See Gnanasambandam [0115] the system uses knowledge graphs that connect various symptoms with potential conditions/diseases. [0116] if a person exhibits certain symptoms and has certain laboratory tests performed, then that person may have a certain medical condition (e.g., type 2 diabetes mellitus) that is identified in the knowledge graphs using the logical structures. See also [0266].).
The system of Gnanasambandam is applicable to the disclosure of Johnson as they both share characteristics and capabilities, namely, they are directed to processing patient related questions and answers. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Johnson to include elements as taught by Gnanasambandam. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Johnson in order to improve the health outcomes of a group by improving clinical outcomes while lowering costs (see Gnanasambandam [0002]).
Regarding claim 15, Johnson discloses One or more memories collectively storing an analytic method performance data structure reflecting performance of an analytic method with respect to a particular patient, the data structure comprising:
relative to an analytic method definition specifying a plurality of questions, for each of which it specifies a plurality of possible answers (See Johnson Fig. 2 and [0030] system can use decision trees of questions connected to possible answers and final recommendations. [0035] if the user provides a first answer to a first question, a first subset of second questions may follow. However, if the user provides a second answer, different from the first answer, a second subset of second questions may follow.),
one or more entries, each entry identifying one of the plurality of questions and a possible answer that was selected for the identified questions (See Johnson [0034] Based at least in part upon one or more answers to the first questions, one or more second questions can be determined and provided to the user. The user can be classified into one or more categories based at least in part upon answers provided to the first questions and the second questions. A recommendation for the user can be generated based at least in part upon the classification of the user. [0035] if the user provides a first answer to a first question, a first subset of second questions may follow. However, if the user provides a second answer, different from the first answer, a second subset of second questions may follow.),
a first one of the one or more entries having been added to the data structure in response to automatic selection of the possible answer for the corresponding question (See Johnson [0035] for example, if the user provides a first answer to a first question, a first subset of second questions may follow. However, if the user provides a second answer, different from the first answer, a second subset of second questions may follow.) based upon application of a natural language understanding mechanism to a representation of a … conversation discussing the patient at a time when the first question was pending (See Johnson [0036] after a question is posed to the user, the user may provide an open-form answer, which may then be evaluated using one or more machine learning systems, such as a large language model, to extract salient information for processing. This answer is in response to a pending first question.),
such that the contents of the data structure are usable to select one of a plurality of possible recommended actions specified by the analytic method definition (See Johnson [0035] for example, if the user provides a first answer to a first question, a first subset of second questions may follow. However, if the user provides a second answer, different from the first answer, a second subset of second questions may follow.).
Johnson does not disclose:
the conversation is a spoken conversation.
Gnanasambandam teaches:
the conversation is a spoken conversation (See Gnanasambandam [0175] the system receives text questions and answers via text input through a microphone (e.g., words spoken into the user device).).
The system of Gnanasambandam is applicable to the disclosure of Johnson as they both share characteristics and capabilities, namely, they are directed to processing patient related questions and answers. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Johnson to include elements as taught by Gnanasambandam. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Johnson in order to improve the health outcomes of a group by improving clinical outcomes while lowering costs (see Gnanasambandam [0002]).
Regarding claim 16, Johnson in view of Gnanasambandam discloses the memories of claim 15 as discussed above. Johnson further discloses a memories, wherein:
a second one of the one or more entries was added to the data structure in response to user input explicitly selecting the possible answer indicated by the second entry for the corresponding question (See Fig. 1B and Johnson [0036] questions may be presented to the user in the form of a limited set of responses that correspond to an input. For example, a first question may include a list of potential answers and a user input may correspond to selection of one or more of the potential answers.).
Regarding claim 17, Johnson in view of Gnanasambandam discloses the memories of claim 15 as discussed above. Johnson further discloses a memories, wherein:
a second one of the one or more entries was added to the data structure in response to automatic selection of the indicated possible answer for the corresponding question based upon application of a natural language understanding mechanism to a representation of a spoken conversation discussing the patient at a time before the first question was pending (See Johnson [0036] after a question is posed to the user, the user may provide an open-form answer, which may then be evaluated using one or more machine learning systems, such as a large language model, to extract salient information for processing. This answer is in response to a pending first question.).
Regarding claims 18-20, Johnson in view of Gnanasambandam discloses the system of claims 1, 11, and 13, as discussed above. Claims 18-20 recite computer-readable media storing a method that is substantially similar to the method of claims 1, 11, and 13. Accordingly, claims 18-20 are rejected based on the same analysis.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Huyn et al. (U.S. 2002/0035486) teaches a system and method for a computerized clinical questionnaire with dynamically presented questions.
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/B.L.H./Examiner, Art Unit 3684
/Shahid Merchant/Supervisory Patent Examiner, Art Unit 3684