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 .
Claim Rejections - 35 USC § 112
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.
Claim 9 is 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 9 recites the limitation "…wherein the model is trained…". There is insufficient antecedent basis for this limitation in the claim.
The terms “general corpus” and “specialized corpus” in claim 9 are relative terms which renders the claim indefinite. The terms “general corpus” and “specialized corpus” are not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Independent claim 12 recites (additional limitations crossed out):
in response to a consultation initiating operation, providing an interaction interface of a user and a
determining, based on at least one round of conversation between the user and the
in response to determining that the information collection requirement for the health consultation is satisfied, providing an anticipated health recommendation for the health consultation of the user at the interaction interface.
The above limitations, as drafted, are processes that, under their broadest reasonable interpretation, is a process that, under its broadest reasonable interpretation covers managing personal behavior or relationships or interactions between people, as well as performance of limitations by the human mind or with pen and paper. That is, other than reciting the claims as being performed by an “electronic device” and a “digital” assistant, nothing in the claims precludes the steps as being described as managing personal behavior or relationships or interactions between people, or performance of limitations by the human mind or with pen and paper. The claims, as written describe providing an interaction interface of a user and an assistant (i.e., medical professional) for a health consultation, determining if enough information has been gathered during a conversation between the user and the assistant, and providing a health recommendation if enough information has been gathered. If a claim limitation, under its broadest reasonable interpretation, describes managing personal behavior or relationships or interactions between people, then it falls within the “Certain Methods of Organizing Human Activities” grouping of abstract ideas. Further, if a claim limitation, under its broadest reasonable interpretation, describes steps that may be performed mentally or with pen and paper, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of an “electronic device” to perform the steps. This additional element is recited at a high level of generality (see at least paragraph [0089]) such that it amounts to no more than mere instructions to apply the exception using generic computing components. The claims further recite that the assistant is “digital”. However, this merely serves to link the judicial exception (i.e., collaboration with a medical professional) to a particular technological environment or field of use (i.e., computer environment). 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. The claims are therefore still directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of an “electronic device” to perform the claimed steps amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Therefore, the claims are not found to be patent eligible.
Claims 1 and 20 feature limitations similar to those of claim 12, and are therefore also found to be directed to an abstract idea without significantly more.
Claims 2-11 are dependent on claim 1, and include all the limitations of claim 1. Claims 13-19 are dependent on claim 12, and include all the limitations of claim 12. Therefore, they are also found to be directed to an abstract idea. Claims 4-6 disclose providing input to a “model” and receiving an output. Claim 9 discloses training of said “model”. However the “model” is recited at a high level of generality and may reasonably be considered an additional abstract idea in the “mental process” category. The remaining dependent claims have not been found to integrate the judicial exception into a practical application, or provide significantly more than the abstract idea since they merely further narrow the abstract idea. Therefore, the dependent claims are found to be directed to an abstract idea without significantly more
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-6, 8-10, 12-17, and 19-20 is/are rejected under 35 U.S.C. 102(a)(1)as being anticipated by Gnanasambandam (WO 2021/071971)
Regarding claim 1, Gnanasambandam discloses A method for information interaction, comprising:
in response to a consultation initiating operation, providing an interaction interface of a user and a digital assistant for a health consultation of the user; (See at least Figs. 9-10)
determining, based on at least one round of conversation between the user and the digital assistant in the interaction interface, whether an information collection requirement for the health consultation is satisfied; and (See at least Para. [0193] – “Follow up questions presented to the user (the second set of follow-up questions) are asked using natural language and are specifically formulated ("dynamically formulated question") to elicit a response that will inform or fulfill an identified parameter. Each dynamically formulated question can target one parameter at a time. When answers are received from the user in response to a dynamically formulated question, the cognitive intelligence platform 102 inserts the answer into the workspace.”, and [0195] – “In this first round of analysis, the cognitive intelligence platform 102 consolidates the first and second data in the workspace and determines if additional parameters need to be identified, or if sufficient information is present in the workspace to answer the originating question. In some embodiments, the cognitive agent 110 (FIG. 1) assesses the data in the workspace and queries the cognitive agent 110 to determine if the cognitive agent 110 needs more data in order to answer the originating question. The conversation orchestrator 124 executes as an interface.”
in response to determining that the information collection requirement for the health consultation is satisfied, providing an anticipated health recommendation for the health consultation of the user at the interaction interface. (See at least Para. [0199] – “Subsequent to determining enough information is present in the workspace to answer the originating question, the cognitive agent 110 answers the question, and additionally can suggest a recommendation or a recommendation (e.g., line 418). The cognitive agent 110 suggests the reference or the recommendation based on the context and questions being discussed in the conversation (e.g., conversation 400). The reference or recommendation serves as additional handout material to the user and is provided for informational purposes. The reference or recommendation often educates the user about the overall topic related to the originating question.”
Regarding claim 2, Gnanasambandam discloses The method of claim 1, further comprising: in response to determining that the information collection requirement for the health consultation is not satisfied, providing a guidance reply of the digital assistant to guide the user to input further information for the health consultation. (See at least Para. [0200] – “In the example illustrated in FIG. 4, in response to receiving the originating questions (line 402), the cognitive intelligence platform 102 (e.g., the cognitive agent 110 in conjunction with the critical thinking engine 108) parses the originating question to determine at least one parameter: location. The cognitive intelligence platform 102 categorizes this parameter, and a corresponding dynamically formulated question in the second set of follow-up questions. Accordingly, in lines 404 and 406, the cognitive agent 110 responds by notifying the user "I can certainly check this ... " and asking the dynamically formulated question "I need some additional information in order to answer this question, was this an in-home glucose test or was it done by a lab or testing service?"”.
Regarding claim 3, Gnanasambandam discloses The method of claim 1, in the at least one round of conversation, further comprising:
in response to receiving a first query of the user, generating a first reply to the first query based at least on the first query; and
providing the first reply at the interaction interface.
(See at least Fig. 4)
Regarding claim 4, Gnanasambandam discloses The method of claim 3, wherein generating the first reply comprises:
generating a prompt input corresponding to the first query based at least on a prompt bank for the digital assistant;
providing the prompt input to a model to obtain an output of the model; and
determining the first reply based on the output of the model.
(See at least Para. [0339] – “In some embodiments, the server may receive text input by the patient. For example, the text input by the user may include symptoms the patient is experiencing and ask a question pertaining to what medical condition the patient may have.”, Para. [0340] – “At block 2504, the processing device may process the notes to obtain indicia including a subject, an object, a word, a cardinal, a phrase, a concept, a sentence, a predicate, or some combination thereof. Textual analysis may be performed to extract the indicia. Processing the patient notes to obtain the indicia may further include inputting the notes into an artificial intelligence engine 109 trained to identify the indicia in text based on commonly used indicia pertaining to the possible medical condition. The artificial intelligence engine 109 may determine commonly used indicia for various medical conditions based on evidence-based guidelines, clinical trial results, physician research, or the like that are input to one or more machine learning models.”, Para. [0341] – “At block 2506, the processing device may identify a possible medical condition of the patient by identifying a similarity between the indicia and a knowledge graph representing knowledge pertaining to the possible medical condition. The knowledge graph may include a set of nodes representing the set of information pertaining to the possible medical condition. The set of nodes may also include relationships (e.g., predicates) between the set of information pertaining to the possible medication condition. In some embodiments, identifying the possible medical condition may include using a cognified data structure generated from the notes of the patient. The cognified data structure may include a conclusion based on a logic structure representing evidence based guidelines pertaining to the possible medical condition.”, and Para. [0345] – “At block 2508, the processing device may provide, at a first time, first information of the set of information to a computing device of the patient for presentation of the computing device, the first information being associated with a root node of the set of nodes. In some embodiments, the first information may pertain to a name of the possible medical condition.”
Regarding claim 5, Gnanasambandam discloses The method of claim 4, wherein determining the first reply based on the output of the model comprises:
determining whether the output of the model satisfies a predetermined medical verification rule; and
in response to the output of the model satisfying the medical verification rule, determining the first reply based on the output of the model.
(See at least Para. [0341] – “At block 2506, the processing device may identify a possible medical condition of the patient by identifying a similarity between the indicia and a knowledge graph representing knowledge pertaining to the possible medical condition.”, and Para. [0345] – “At block 2508, the processing device may provide, at a first time, first information of the set of information to a computing device of the patient for presentation of the computing device, the first information being associated with a root node of the set of nodes. In some embodiments, the first information may pertain to a name of the possible medical condition.)
Regarding claim 6, Gnanasambandam discloses The method of claim 5, further comprising:
in response to the output of the model failing to satisfy the medical verification rule, modifying the prompt input;
providing the modified prompt input to the model to obtain a further output of the model; and determining the first reply based on the further output of the model.
(See at least Para. [0364] – “At block 3108, the processing device may provide the diagnosis to a computing device of a patient and/or a physician for presentation on the computing device. The diagnosis may be included in the cognified data. The physician may review the diagnosis and may provide feedback via graphical element(s) whether the diagnosis is accurate. The feedback may be received by the artificial intelligence engine 109 and used to update the one or more machine learning models used by the artificial intelligence engine 109 to cognify data and generate diagnoses.”, and Para. [0345] – “At block 2508, the processing device may provide, at a first time, first information of the set of information to a computing device of the patient for presentation of the computing device, the first information being associated with a root node of the set of nodes. In some embodiments, the first information may pertain to a name of the possible medical condition.”
Regarding claim 8, Gnanasambandam discloses The method of claim 1, wherein a reply of the digital assistant in the at least one round of conversation is used to guide the user to provide at least one class of health information. (See at least Fig. 4, Item 406.)
Regarding claim 9, in light of the 112 rejection, Gnanasambandam discloses The method of claim 1, wherein the model is trained based on a general corpus and a specialized corpus for medical field. (See at least Para. [0367] – “The artificial intelligence engine 109 may be trained on evidence-based guidelines that correlate the various information with the particular stages. For example, it may be known that a particular stage of cancer involves symptoms such as weight loss, lack of appetite, bone pain, dry cough or shortness of breath, or some combination thereof. If those symptoms are identified for the medical condition diagnosed (cancer) for the patient, then that particular stage may be determined.”)
Regarding claim 10, Gnanasambandam discloses The method of claim 1, wherein providing the interaction interface comprises: displaying identification information of a target consultation object in a predetermined area of the interaction interface, an object of the health consultation being the target consultation object. (See at least Fig. 8A’s “Nathan’s Profile”; also see Para. [0390] – “Also, an image 4014 of a face of the person on the image 4012 of the driver's license may be extracted and used for a profile picture of the user.”)
Claims 12 and 20 feature limitations similar to those of claim 1, and are therefore rejected using the same rationale.
Claim 13 features limitations similar to those of claim 2, and is therefore rejected using the same rationale.
Claim 14 features limitations similar to those of claim 3, and is therefore rejected using the same rationale.
Claim 15 features limitations similar to those of claim 4, and is therefore rejected using the same rationale.
Claim 16 features limitations similar to those of claim 5, and is therefore rejected using the same rationale.
Claim 17 features limitations similar to those of claim 6, and is therefore rejected using the same rationale.
Claim 19 features limitations similar to those of claim 8, and is therefore rejected using the same rationale.
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.
Claim(s) 7 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gnanasambandam in view of Borsutsky (US 2018/0096686).
Regarding claim 7, Gnanasambandam does not explicitly disclose The method of claim 1, further comprising:
providing at least one category label of a query example at the interaction interface; and
providing, based on a target category label in the at least one category label being selected, at least one query example under the target category label at the interaction interface.
(See at least Borsutsky, Para. [0049] – “FIGS. 20 and 21 illustrate an exemplary conversation, in a simplified and abbreviated form, that a user has with an exemplary chatbot that is employed by a pizzeria (namely Joe's Pizza) according to the chatbot communication technique implementations described herein. As exemplified in FIG. 20, the conversation 2000 starts with the user submitting the query “Hi” to the chatbot. The chatbot responds to this query with the welcome message “Welcome to Joe's Pizza. I can take your order, make a reservation, or answer any questions you have. How can I help you?” The chatbot's query response also includes an initial menu 2002 that lists the actions that the user can perform (namely, the user can place an order for Joe's Pizza, get the hours that Joe's Pizza is open, make a reservation for Joe's Pizza, and get contact information for Joe's Pizza).”, and Figs. 20-21. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Gnanasambandam to utilize the teachings of Bosutsky since they are in the same field of endeavor (i.e., interaction with virtual agents/chatbots), and all of the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions and the combination would have yielded predictable results to one of ordinary skill in the art at the time of the invention.
Claim 18 features limitations similar to those of claim 7, and is therefore rejected using the same rationale.
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gnanasambandam in view of Ramalingam (US 2023/0325893)
Regarding claim 11, Gnanasambandam does not explicitly disclose The method of claim 10, further comprising:
in response to the consultation initiating operation, providing a confirmation request for the target consultation object; and
in response to receiving the confirmation for the target consultation object, determining that the object of the health consultation is the target consultation object. (See at least Ramalingam, Para. [0015] – “Initially, the chatbot may request for authentication data from the consumer via the messaging application. In response, using the messaging application, the consumer may provide any type of authentication data needed for identity verification to the chatbot. Upon verification of the consumer's identity, the chatbot may match the consumer with associated billers from stored consumer billing data and, display one or more options to view a particular payment request (e.g., a bill, an invoice, etc.) via the messaging application, such as in the form of light bill data (e.g., text information of an invoice) or a Uniform Resource Locator (URL) that links to a full invoice.” It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Gnanasambandam to utilize the teachings of Ramalingam since it would ensure privacy of the user’s data.
Conclusion
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/KYLE G ROBINSON/Examiner, Art Unit 3685
/MARK HOLCOMB/Primary Examiner, Art Unit 3685
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