DETAILED ACTION
This communication is in response to the Amendments and Arguments filed on 11/19/2025. Claims 1-20 are pending and have been examined. Hence, this action has been made FINAL.
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 .
Information Disclosure Statement
The IDS dated 11/03/2025 has been considered and placed in the application file.
Response to Arguments
The reply filed on 11/19/2025 has been entered. Applicant’s arguments with respect to claims 1-20 have been considered but are not persuasive/moot in view of new ground(s) of rejection caused by the amendments.
With respect to the applicant’s arguments to claim rejections under 35 U.S.C § 101, Applicant has amended each of the independent claims and asserts that “Claim 1 includes neural networks and machine models. directed to generating a predictive model using an artificial neural network with weighted nodes. This is clearly not a mental process as claim 1 is explicitly directed to an implementation of an artificial neural network.” The examiner respectfully disagrees with these assertions. The limitation of a “neural network” is recited at a high level of generality (¶ [0093]) and thus merely equate to “apply it” or otherwise merely uses a generic computer as a tool to perform an abstract which are not indicative of integration into a practical application as per MPEP 2106.05(f). Further details can be found below with respect to rejections under 35 U.S.C. § 101.
Applicant further asserts that “Claim 1 is similar to Example 47 from the USPTO's updated Subject Matter Eligibility Guidance to AI Inventions. Like Example 47, claim 1 is directed to device and is a practical application, e.g., using an artificial neural network to implement the present method steps to more efficiently find matching providers than what could be done by a person ( e.g., the patient user).” The examiner respectfully disagrees with these assertions. Claim 3 of Example 47 from the USPTO’s updated Subject Matter Eligibility Guidance to AI Inventions illustrates that the artificial neural network is only integrated into practical application because the claim limitations of Claim 3 “detects network intrusions and takes real-time remedial actions, including dropping suspicious packets and blocking traffic from suspicious source addresses. … The claimed invention reflects this improvement in the technical field of network intrusion detection.” In other words, Claim 3’s limitations are integrated into practical application because they perform an improvement in the technical field of the invention. Further, Claim 2 of Example 47 from the USPTO’s updated Subject Matter Eligibility Guidance to AI Inventions asserts that “’using the trained ANN’ provide nothing more than mere instructions to implement an abstract idea on a generic computer.” As amended, there is no language in the independent claims of the instant application that recite a practical application of the invention, nor is there any language in the independent claims of the instant application that limit the invention beyond “using the artificial neural network.”
With respect to the applicant’s arguments to claim rejections under 35 U.S.C § 102 and 103, the applicant’s arguments with respect to claims 1-20 have been considered but are moot in view of new ground(s) of rejection caused by the amendments.
With respect to the applicant’s arguments to the double patenting rejections, the applicant’s arguments with respect to claims 1-20 have been considered but are moot in view of new ground(s) of rejection caused by the amendments.
Claim Objections
Claims 1, 13, and 20 is/are objected to because of the following informalities:
Claim 1, line 8, should be “search results related to the provider search query”
Claims 13 and 20 are objected to for similar reasons to claim 1
Claim(s) 2-12 and 14-19 depend either directly or indirectly from the objection of claims 1 and 13, therefore they are also objected.
Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-4, 6, 7, 10-16, and 18-20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 3, 5, 7, 10, and 19 of co-pending Application No. 17/533,993 (reference application) in view of US Patent Publication 20200226475 A1 (Ma et al.). Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of the reference application are narrower than the claims of the instant application, therefore the claims of the instant application are obvious in view of the claims of the reference application. Please see the table below for the claim mappings.
Instant Application: 18/387,690
Reference Application: 17/533,993
Claim 1: A method comprising:
receiving a provider search query from a patient user on a client device;
based on the provider search query, generating a set of supplemental questions using a machine model to develop vector inputs to an artificial neural network in circuitry;
receiving a set of responses to the set of supplemental questions;
based on the set of responses and a location of the client device, identifying a set of search results related to the query using the artificial neural network;
for each search result in the identified set of search results:
determining a probability that the patient user will select a provider associated with the search result based on a set of patient data associated with the patient user and a set of provider data associated with the provider, and
ranking the search result based on the determined probability and a set of system preference criteria; and
causing display of the ranked set of search results on a graphical user interface of the client device.
Claim 1: A method comprising:
receiving, via a network, a query from a patient user on a client device;
based on the query and a location of the client device, accessing, via the network, medical claim data from a database;
automatically determining a set of secondary patient user locations based on characteristics of the medical claim data and the location of the client device, wherein:
determining the set of secondary patient user locations includes:
analyzing a set of secondary patient data in parallel, selecting a city based on proximity to the location of the client device, and calculating a centroid for the selected city, and the set of secondary patient user locations is associated with a set of secondary patients;
identifying a set of search results related to the query, wherein the set of search results is associated with the set of secondary patient user locations;
for a respective search result in the set of search results:
determining, using a predictive model trained to analyze a set of patient data associated with the patient user and a set of provider data associated with a provider, a probability that the patient user will select the provider associated with the respective search result based on:
the set of patient data associated with the patient user, and
the set of provider data associated with the provider, and
automatically ranking the respective search result based on the determined probability and a set of system preference criteria;
displaying the set of search results organized by ranking on a graphical user interface of the client device; and
in response to a determination that a subset of the set of search results is associated with a probability above a probability threshold, automatically prompting the patient user to schedule an appointment with the subset of the set of search results.
Claim 1
Claim 1 of the reference application recites all of the limitations of claim 1 of the instant application except “generating a set of supplemental questions using a machine model to develop vector inputs to an artificial neural network in circuitry” and “receiving a set of responses to the set of supplemental questions”.
However, Ma et al. discloses generating a set of supplemental questions (Ma et al. ¶ [0048], "In response to an entry query from the user seeking information to direct the user to a desired website link or to contact information for the department or specialist, the chatbot may respond with questions that progressively focus the responses towards a final answer that satisfies the user's search.") using a machine model (Ma et al. ¶ [0059], " To generate dialog in response to input queries, queries may be input to the neural network 300 which results in a yield of a plurality of outputs." A neural network is considered analogous to a machine model) to develop vector inputs to an artificial neural network in circuitry (Ma et al. ¶ [0018], "The [variational autoencoder] may convert queries received by the chatbot to vectors that are then used by the neural network to generate a response.").
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to include Ma et al.’s supplemental question generation within the method of claim 1 of the reference application because such a modification is the result of combining prior art elements according to known methods to yield predictable results. More specifically, the method of claim 1 of the reference application as modified by Ma et al.’s supplemental question generation can yield a predictable result of providing improved assistance to a patient since supplemental questions would yield greater insight into a patient’s intention and condition. Thus, a person of ordinary skill would have appreciated including in the method of claim 1 of the reference application the ability to do Ma et al.’s supplemental question generation since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim 2
Claim 1 of the reference application recites all of the limitations of claim 2 of the instant application.
Claim 3
Claim 1 of the reference application recites all of the limitations of claim 3 of the instant application.
Claim 4
Claim 1 of the reference application recites all of the limitations of claim 4 of the instant application.
Claim 6
Claim 1 of the reference application recites all of the limitations of claim 6 of the instant application except “wherein the provider search query comprises a set of search terms, the method further comprising: generating the set of supplemental questions based on a machine analysis of the set of search terms from the provider search query.”
However, Ma et al. discloses wherein the provider search query comprises a set of search terms (Ma et al. ¶ [0049], "the user may be seeking a suitable provider for a specific set of symptoms. The user may enter a request to find a provider into the dialog box of the chatbot." A specific set of symptoms is considered analogous to a set of search terms), the method further comprising:
generating the set of supplemental questions based on a machine analysis (Ma et al. ¶ [0086], "a chatbot may generate appropriate, meaning, and engaging responses to input queries posed by clients to a user interface by using a frame architecture that comprises a variational autoencoder (VAE) and generative adversarial network (GAN).") of the set of search terms from the provider search query (Ma et al. ¶ [0049], "If the chatbot is unable to identify a suitable provider based on the set of symptoms, the chatbot may request additional, more specific information from the user to assist in guiding the chatbot to find the provider.").
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to include Ma et al.’s supplemental question generation within the method of claim 1 of the reference application.
The suggestion/motivation for doing so is similar to the suggestion/motivation described above with respect to claim 1.
Claim 7
Claim 1 of the reference application recites all of the limitations of claim 7 of the instant application.
Claim 10
Claim 5 of the reference application recites all of the limitations of claim 10 of the instant application.
Claim 11
Claim 1 of the reference application recites all of the limitations of claim 11 of the instant application.
Claim 12
Claim 7 of the reference application recites all of the limitations of claim 12 of the instant application.
Claim 13
Claim 10 of the reference application recites all of the limitations of claim 13 of the instant application except “generating a set of supplemental questions using a machine model to develop vector inputs to an artificial neural network in circuitry” and “receiving a set of responses to the set of supplemental questions”.
However, Ma et al. discloses generating a set of supplemental questions (Ma et al. ¶ [0048], "In response to an entry query from the user seeking information to direct the user to a desired website link or to contact information for the department or specialist, the chatbot may respond with questions that progressively focus the responses towards a final answer that satisfies the user's search.") using a machine model (Ma et al. ¶ [0059], " To generate dialog in response to input queries, queries may be input to the neural network 300 which results in a yield of a plurality of outputs." A neural network is considered analogous to a machine model) to develop vector inputs to an artificial neural network in circuitry (Ma et al. ¶ [0018], "The [variational autoencoder] may convert queries received by the chatbot to vectors that are then used by the neural network to generate a response.").
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to include Ma et al.’s supplemental question generation within the method of claim 10 of the reference application.
The suggestion/motivation for doing so is similar to the suggestion/motivation described above with respect to claim 1.
Claim 14
Claim 10 of the reference application recites all of the limitations of claim 14 of the instant application.
Claim 15
Claim 10 of the reference application recites all of the limitations of claim 15 of the instant application.
Claim 16
Claim 10 of the reference application recites all of the limitations of claim 16 of the instant application.
Claim 18
Claim 10 of the reference application recites all of the limitations of claim 18 of the instant application except “wherein the provider search query comprises a set of search terms, the method further comprising: generating the set of supplemental questions based on a machine analysis of the set of search terms from the provider search query.”
However, Ma et al. discloses wherein the provider search query comprises a set of search terms (Ma et al. ¶ [0049], "the user may be seeking a suitable provider for a specific set of symptoms. The user may enter a request to find a provider into the dialog box of the chatbot." A specific set of symptoms is considered analogous to a set of search terms), the method further comprising:
generating the set of supplemental questions based on a machine analysis (Ma et al. ¶ [0086], "a chatbot may generate appropriate, meaning, and engaging responses to input queries posed by clients to a user interface by using a frame architecture that comprises a variational autoencoder (VAE) and generative adversarial network (GAN).") of the set of search terms from the provider search query (Ma et al. ¶ [0049], "If the chatbot is unable to identify a suitable provider based on the set of symptoms, the chatbot may request additional, more specific information from the user to assist in guiding the chatbot to find the provider.").
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to include Ma et al.’s supplemental question generation within the method of claim 10 of the reference application.
The suggestion/motivation for doing so is similar to the suggestion/motivation described above with respect to claim 1.
Claim 19
Claim 10 of the reference application recites all of the limitations of claim 19 of the instant application.
Claim 20
Claim 19 of the reference application recites all of the limitations of claim 20 of the instant application except “generating a set of supplemental questions using a machine model to develop vector inputs to an artificial neural network in circuitry” and “receiving a set of responses to the set of supplemental questions”.
However, Ma et al. discloses generating a set of supplemental questions (Ma et al. ¶ [0048], "In response to an entry query from the user seeking information to direct the user to a desired website link or to contact information for the department or specialist, the chatbot may respond with questions that progressively focus the responses towards a final answer that satisfies the user's search.") using a machine model (Ma et al. ¶ [0059], " To generate dialog in response to input queries, queries may be input to the neural network 300 which results in a yield of a plurality of outputs." A neural network is considered analogous to a machine model) to develop vector inputs to an artificial neural network in circuitry (Ma et al. ¶ [0018], "The [variational autoencoder] may convert queries received by the chatbot to vectors that are then used by the neural network to generate a response.").
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to include Ma et al.’s supplemental question generation within the method of claim 19 of the reference application.
The suggestion/motivation for doing so is similar to the suggestion/motivation described above with respect to claim 1.
Claims 5, 9, and 17 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 3 of co-pending Application No. 17/533,993 (reference application) in view of US Patent Publication 20200226475 A1 (Ma et al.) in view of US Patent Publication 20200388402 A1 (Frey et al.). Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of the reference application are narrower than the claims of the instant application, therefore the claims of the instant application are obvious in view of the claims of the reference application.
Claim 5
Claim 1 of the reference application recites all of the limitations as claim 5 of the instant application except “a closest region to the patient user that includes a group of provider types providing the medical care identified by the set of search results inclusive of the set of responses.”
However, Frey et al. discloses wherein the patient user location is based on [a centroid of] a closest region to the patient user that includes a group of provider types providing the medical care identified by the set of search results inclusive of the set of responses (Frey et al. ¶ [0054], "The provider determination system 104 may generate the location request to match the determined type (e.g., communication type (e.g., email, SMS message, audio message, video message, etc.)) of the received inquiry message." ¶ [0064], "Based on the identified location data, the provider determination system 104 determines whether a location identified within the identified location data is within an area of support of the provider determination system 104, as shown in act 240 of FIG. 2C. In particular, the determination system 104 queries a provider database of the provider determination system 104 to determine whether the identified location matches (e.g., falls within) an area (e.g., geographical are) that the provider determination system 104 is currently supporting.").
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify the claim 1 of the reference application to include Frey et al.’s region identification method because such a modification is the result of combining prior art elements according to known methods to yield predictable results. More specifically, claim 1 of the reference application as modified by Frey et al.’s region identification can yield a predictable result of improving provider recommendations since recommendations could encompass providers from an entire region as opposed to being confined to only a city. Thus, a person of ordinary skill would have appreciated including in claim 1 of the reference application the ability to do Frey et al.’s region identification since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim 9
Claim 1 of the reference application recites all of the limitations as claim 5 of the instant application except “causing display of each supplemental question of the set of supplemental questions as selectable user interface elements on the graphical user interface of the client device.”
However, Frey et al. discloses causing display of each supplemental question of the set of supplemental questions as selectable user interface elements on the graphical user interface of the client device (Frey et al. ¶ [0111], "Referring to FIG. 4F, upon adding the request for provider list message within the chat bubble 434 to the communication thread GUI 418 of the messaging application GUI 412a, the client device 402 may detect one or more user interactions inputting content of a provider selection response message in response to the provider list message 434." Figures 4A-4F illustrate displaying multiple supplemental questions as selectable user interface elements on a GUI of the client device.).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify the claim 1 of the reference application to include Frey et al.’s supplemental question GUI because such a modification is the result of combining prior art elements according to known methods to yield predictable results. More specifically, claim 1 of the reference application as modified by Frey et al.’s supplemental question GUI can yield a predictable result of improving user experience since selectable GUI elements would make it easier for a chatbot to guide a user towards a provider recommendation. Thus, a person of ordinary skill would have appreciated including in claim 1 of the reference application the ability to do Frey et al.’s supplemental question GUI since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim 17
Claim 1 of the reference application recites all of the limitations as claim 17 of the instant application except “a closest region to the patient user that includes a group of provider types providing the medical care identified by the set of search results inclusive of the set of responses.”
However, Frey et al. discloses wherein the patient user location is based on [a centroid of] a closest region to the patient user that includes a group of provider types providing the medical care identified by the set of search results inclusive of the set of responses (Frey et al. ¶ [0054], "The provider determination system 104 may generate the location request to match the determined type (e.g., communication type (e.g., email, SMS message, audio message, video message, etc.)) of the received inquiry message." ¶ [0064], "Based on the identified location data, the provider determination system 104 determines whether a location identified within the identified location data is within an area of support of the provider determination system 104, as shown in act 240 of FIG. 2C. In particular, the determination system 104 queries a provider database of the provider determination system 104 to determine whether the identified location matches (e.g., falls within) an area (e.g., geographical are) that the provider determination system 104 is currently supporting.").
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify the claim 1 of the reference application to include Frey et al.’s region identification method.
The suggestion/motivation for doing so is similar to the suggestion/motivation described above with respect to claim 5.
Claim 8 is provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 3 of co-pending Application No. 17/533,993 (reference application) in view of US Patent Publication 20210043320 A1 (Ma et al.) in view of US Patent Publication 20190043606 A1 (Roots et al.). Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of the reference application are narrower than the claims of the instant application, therefore the claims of the instant application are obvious in view of the claims of the reference application.
Claim 8
Claim 3 of the reference application recites all of the limitations as claim 8 of the instant application except “patient insights.” However, Roots et al. discloses generating the probability using the predictive model (Roots et al. ¶ [0075]-[0077], "the model predicting subsystem scores the optimal provider match(es) for a specific patient/member. ... In an embodiment, the predictive engine relies on the values of the feature space for determining optimal matches." ¶ [0067], "It is envisioned that multiple aggregate internal review scores and multiple aggregate external review scores will be incorporated in the feature space") trained to analyze patient insights associated with the provider (Roots et al. ¶ [0059], "In a preferred embodiment, the preprocessing system also ingests internal data about the provider. Internal data refers to data and metadata generated by the patients/members and providers that are existing users of the platform rather than third party data." Internal patient data associated with a provider is considered analogous to patient insights associated with a provider; ¶ [0074], "In an embodiment of the present invention, the model training and testing subsystem consumes, preferably asynchronously, the preprocessed data discussed above, commonly referred to as training data, as directed by the application service. The trained and verified model is then serialized and available for real-time model fitting.").
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify the claim 3 of the reference application to include Roots et al.’s patient insights because such a modification is the result of combining prior art elements according to known methods to yield predictable results. More specifically, claim 3 of the reference application as modified by Roots et al.’s patient insights can yield a predictable result of improving provider recommendations since a predictive model could better understand and consider patient insights when predicting a match between a patient and a provider. Thus, a person of ordinary skill would have appreciated including in claim 3 of the reference application the ability to do Roots et al.’s patient insights since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
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. All of the claims are method claims (1-12), apparatus/machine claims (13-20) or manufacture claim under (Step 1), but under Step 2A all of these claims recite abstract ideas and specifically mental processes. These mental processes are more particularly recited in claims 1, 13, and 20 as:
generating a set of supplemental questions using a machine model…
developing vector inputs to an artificial neural network…
receiving a set of responses to the set of supplemental questions…
identifying a set of search results related to the query…
determining a probability that the patient user will select a provider associated with the search result…
ranking the search result based on the determined probability and a set of system preference criteria…
Under Step 2A Prong One, claims 1, 13, and 20 are directed to an abstract idea and specifically a mental process. As detailed above, the steps of generating, identifying, determining, ranking, etc. may be practically performed in the human mind with the use of a physical aid such as a pen and paper. For example, a receptionist could receive a provider search query from a patient looking for providers in the area, ask additional questions for clarification, identify a list of medical providers based on the patient’s answers and their home location, determine which provider would be best for the patient given their needs, and then rank each provider for the patient to view and select from.
Under Step 2A Prong Two, this judicial exception is not integrated into a practical application because claims 1-20 do not recite additional elements that integrate the exception into a practical application. In particular, claims 1, 13, and 20 recite the additional elements of a client device (¶ [0021]), a graphical user interface (¶ [0042]), a processor (¶ [0082]), memory storing instructions(¶ [0083]), computer-readable storage medium (¶ [0102]), a machine model (¶ [0050]), and an artificial neural network (¶ [0093]). These additional elements are recited at a high level of generality and merely equate to “apply it” or otherwise merely uses a generic computer as a tool to perform an abstract which are not indicative of integration into a practical application as per MPEP 2106.05(f). Further, claims 1, 13, and 20 recite the additional elements of “receiving a query…” and “causing display…”, both of which amount to insignificant extra-solution activities which are not indicative of integration into a practical application as per MPEP 2106.05(g). 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 claim is directed to an abstract idea.
Under Step 2B, the claims do not recite additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements of using a computer is noted as a general computer {client device (¶ [0021]); graphical user interface (¶ [0042]); processor (¶ [0082]); memory storing instructions(¶ [0083]); computer-readable storage medium (¶ [0102])}. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Further, the additional limitations in the claims noted above are directed towards insignificant extra-solution activities. The claims are not patent eligible.
With respect to claims 2-5 and 14-17, the claim relates to accessing medical claim data to determine patient location, and then using that location data to improve provider search results. This relates to a receptionist accessing patient claim data in order to determine a provider within an optimal location for the patient. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 6 and 18, the claim relates to generating supplemental questions based on analyzing search terms in the patient query. This relates to a receptionist asking the patient to clarify a condition they specified in their initial query. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 7-8, 10, and 19, the claim relates to using a predictive model trained on patient data and provider data to predict which providers would best suit a patient. This relates to a receptionist comparing multiple providers’ data, including external user reviews, to a patient’s data in order to determine a provider that best suits the patient. The additional limitations of a “predictive model” and “natural language processor” are recited at a high level of generality {predictive model (¶ [0050]); natural language processor (¶ [0059], Figure 5)} and merely equate to “apply it” or otherwise merely uses a generic computer as a tool to perform an abstract which are not indicative of integration into a practical application as per MPEP 2106.05(f). No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 9, the claim relates to displaying supplemental questions to a user via a graphical user interface. This relates to a receptionist providing a user with a written list of supplemental questions about their query. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 11, the claim relates to determining that the number of search results exceeds a threshold. This relates to a receptionist finding at least twenty providers based on the patient’s query and location data. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 12, the claim relates to receiving a provider selection from the client device after providing the search results. This limitation amounts to insignificant extra-solution activities which are not indicative of integration into a practical application as per MPEP 2106.05(g). No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
For all of the above reasons, taken alone or in combination, claims 1-20 recite a non-statutory mental process.
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.
Claims 1, 6, 11-13, and 18 are rejected under 35 U.S.C. 103 as obvious over US Patent Publication 20150278222 A1, (Claussenelias et al.) in view of US Patent Publication US 20200226475 A1 (Ma et al.).
Claim 1
Regarding claim 1, Claussenelias et al. disclose a method, comprising:
receiving a query from a patient user on a client device (Claussenelias et al. ¶ [0030], "a user may select search prompt 204 and use textbox 210 to search the provider by name, area of specialty, conditions treated, procedures performed, or textbox 212 to search by city/state.");
based on [the set of responses and] a location of the client device, identifying a set of search results related to the query (Claussenelias et al. ¶ [0034], "In some embodiments, a location of the user is always part of the search process ... That search location is used in combination with other search criteria to filter the providers that satisfy the search.");
for each search result in the identified set of search results:
determining a probability that the patient user will select a provider associated with the search result (Claussenelias et al. ¶ [0083], "FIG. 8 is a flowchart illustrating the process 800 for using boost scores to rank search results for a DCP search, such as a search for providers who treat Male Breast Cancer (condition) near Tampa Fla." ¶ [0098], “the expertise of the physician performing the procedure may be significantly more important to the user than the distance to the physician. As such, the statistical weight and/or boost assigned to the location value may be low, e.g., 0.1 on a scale of 0.0 to 1.0, compared to other scored values in the search.” A boost score is considered analogous to a probability.) based on a set of patient data associated with the patient user (Claussenelias et al. ¶ [0034], "In some embodiments, a location of the user is always part of the search process. For instance, if no search location or search location is provided, one is determined based on last known information about the user or some previous search request. That search location is used in combination with other search criteria to filter the providers that satisfy the search." The location of the user is considered analogous to a set of patient data associated with the patient user) and a set of provider data associated with the provider (Claussenelias et al. ¶ [0085], "At step 810, the system determines the certification boost for each provider, which boosts the search results rank of a provider if he or she has one or more board certifications."), and
ranking the search result based on the determined probability and a set of system preference criteria (Claussenelias et al. ¶ [0101], "In a preferred embodiment, providers are ranked by total boost score where the provider with the highest total boost score is ranked first and the provider with the lowest total boost score is ranked last."); and
causing display of the ranked set of search results on a graphical user interface of the client device (Claussenelias et al. Figure 3A shows a ranked set of search results on a graphical user interface.).
Claussenelias et al. do not explicitly disclose all of generating a supplemental set of questions.
However, Ma et al. disclose receiving a provider search query from a patient user on a client device (Ma et al. ¶ [0047], "The user may type in queries in a question format in the query text box 202 to obtain general information about the health provider");
based on the provider search query, generating a set of supplemental questions (Ma et al. ¶ [0048], "In response to an entry query from the user seeking information to direct the user to a desired website link or to contact information for the department or specialist, the chatbot may respond with questions that progressively focus the responses towards a final answer that satisfies the user's search.") using a machine model (Ma et al. ¶ [0059], "To generate dialog in response to input queries, queries may be input to the neural network 300 which results in a yield of a plurality of outputs." A neural network is considered analogous to a machine model) to develop vector inputs to an artificial neural network in circuitry (Ma et al. ¶ [0018], "The [variational autoencoder] may convert queries received by the chatbot to vectors that are then used by the neural network to generate a response.");
receiving a set of responses to the set of supplemental questions (Ma et al. ¶ [0049], "If the chatbot is unable to identify a suitable provider based on the set of symptoms, the chatbot may request additional, more specific information from the user to assist in guiding the chatbot to find the provider." Additional user information regarding a specific set of symptoms is considered analogous to a set of responses); and
based on the set of responses and a location of the client device, identifying a set of search results related to the query (Ma et al. ¶ [0049], "the user may be seeking a suitable provider for a specific set of symptoms. The user may enter a request to find a provider into the dialog box of the chatbot. The chatbot may use the listed symptoms to direct the user to a website (e.g., provide a website link) to a provider matching the symptoms or provide a name, phone number, and/or an address for the provider.") using the artificial neural network (Ma et al. ¶ [0086], "In this way, a chatbot may generate appropriate, meaning, and engaging responses to input queries posed by clients to a user interface by using a frame architecture that comprises a variational autoencoder (VAE) and generative adversarial network (GAN)." Variational autoencoders and generative adversarial networks are considered analogous to artificial neural networks).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify Claussenelias et al.’s provider search system to include Ma et al.’s supplemental question generation because such a modification is the result of combining prior art elements according to known methods to yield predictable results. More specifically, Claussenelias et al.’s provider search system as modified by Ma et al.’s supplemental question generation can yield a predictable result of providing improved assistance to a patient since supplemental questions would yield greater insight into a patient’s intention and condition. Thus, a person of ordinary skill would have appreciated including in Claussenelias et al.’s provider search system the ability to do Ma et al.’s supplemental question generation since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim 6
Regarding claim 6, the rejection of claim 1 is incorporated. Ma et al. further disclose wherein the provider search query comprises a set of search terms (Ma et al. ¶ [0049], "the user may be seeking a suitable provider for a specific set of symptoms. The user may enter a request to find a provider into the dialog box of the chatbot." A specific set of symptoms is considered analogous to a set of search terms), the method further comprising:
generating the set of supplemental questions based on a machine analysis (Ma et al. ¶ [0086], "a chatbot may generate appropriate, meaning, and engaging responses to input queries posed by clients to a user interface by using a frame architecture that comprises a variational autoencoder (VAE) and generative adversarial network (GAN).") of the set of search terms from the provider search query (Ma et al. ¶ [0049], "If the chatbot is unable to identify a suitable provider based on the set of symptoms, the chatbot may request additional, more specific information from the user to assist in guiding the chatbot to find the provider. ").
Claim 11
Regarding claim 11, the rejection of claim 1 is incorporated. Claussenelias et al. further disclose wherein after identifying the set of search results related to the query, the method further comprises:
determining that a size of the set of search results exceeds a threshold amount (Claussenelias et al. ¶ [0059], "In an embodiment, for example, multiple pages of results are returned for a single search. In such a case, the number of healthcare providers displayed per page may be limited to a predefined number, such as 20." Limiting the number of provider results to a predefined number is considered analogous to determining that a size of the set of search results exceeds a threshold amount).
Claim 12
Regarding claim 12, the rejection of claim 1 is incorporated. Claussenelias et al. further disclose wherein after identifying the set of search results related to the query, the method further comprises:
receiving a selection from the client device corresponding to a selected result from the ranked set of search results (Claussenelias et al. ¶ [0080], "Start operation 552 is initiated following user receipt of the search results from a search performed on company webpage 202. From start operation 552, a user may either select a healthcare provider 556 or may first view additional results 554, if any are available.").
Claim 13
Regarding claim 12, Claussenelias et al. disclose a processor (Claussenelias et al. claim 1 discloses "a system for identifying healthcare providers, the system comprising: a processing unit"); and
a memory storing instructions (Claussenelias et al. ¶ [0013], "The various embodiments of the present application may be implemented as a computer process, a computing system or as an article of manufacture, such as a computer program product or computer-readable media. The computer program product may be a computer storage media that is readable by a computer system and is encoding a computer program of instructions for executing a computer process.").
The remaining limitations of claim 13 are similar in scope to the limitations of claim 1 and therefore are rejected for similar reasons as described above.
Claim 18
Regarding claim 18, the rejection of claim 13 is incorporated. The limitations of claim 18 are similar in scope to the limitations of claim 6 and t