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 § 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 1-15 are rejected under 35 U.S.C. §101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
Claim 14 is directed to a method (i.e., a process), claims 1-13 are directed to a device (i.e., a machine), and claim 15 is directed to a computer-readable, non-transitory storage medium (i.e., a machine). Accordingly, claims 1-15 are all within at least one of the four statutory categories.
Step 2A - Prong One:
Regarding Prong One of Step 2A, the claim limitations are to be analyzed to determine whether, under their broadest reasonable interpretation, they “recite” a judicial exception or in other words whether a judicial exception is “set forth” or “described” in the claims. An “abstract idea” judicial exception is subject matter that falls within at least one of the following groupings: a) certain methods of organizing human activity, b) mental processes, and/or c) mathematical concepts.
Representative independent claim 14 includes limitations that recite at least one abstract idea. Specifically, independent claim 14 recites:
14. A medical assistance method executed by a medical assistance device, the method comprising: a step of acquiring personal data including at least one of examination data and medical interview data of a user; and a step of determining a disease state of the user for an individual disease forming a complex disease, based on the personal data, and outputting an improvement target to be achieved by the user to improve a complex disease state, when a combination of the disease states of the individual diseases or a combination of the disease state of the individual disease and the personal data is the complex disease state.
The Examiner submits that the foregoing underlined limitations constitute “a mental process” because a step of acquiring personal data including at least one of examination data and medical interview data of a user; and a step of determining a disease state of the user for an individual disease forming a complex disease, based on the personal data, and outputting an improvement target to be achieved by the user to improve a complex disease state, when a combination of the disease states of the individual diseases or a combination of the disease state of the individual disease and the personal data is the complex disease state amount to observations/evaluations/judgments/analyses that can, at the currently claimed high level of generality, be practically performed in the human mind or via pen and paper.
Accordingly, the claim recites at least one abstract idea.
Step 2A - Prong Two:
Regarding Prong Two of Step 2A, it must be determined whether the claim as a whole integrates the abstract idea into a practical application. It must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
The limitations of claims 1, 14, and 15, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting a device, an acquisition unit, an output unit, a computer-readable non-transitory storage medium, program, and computer to perform the limitations, nothing in the claim elements precludes the steps from practically being performed in the mind. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the device, acquisition unit, output unit, computer-readable non-transitory storage medium, program, and computer are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions of acquiring data, determining data, outputting data) such that it amounts no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (see MPEP § 2106.05). Their collective functions merely provide conventional computer implementation.
Claims 2-13 are ultimately dependent from Claim(s) 1 and include all the limitations of Claim(s) 1. Therefore, claim(s) 2-13 recite the same abstract idea. Claims 2-13 describe further limitations regarding wherein the improvement target includes an improvement target value for an examination value included in the personal data; sets an improvement target for the examination value included in the personal data, based on the combination of the disease states of the individual diseases or the combination of the disease state of the individual disease and the personal data; wherein the personal data includes data relating to a lifestyle habit of the user, and the improvement target includes an improvement target for the lifestyle habit of the user; wherein the lifestyle habit includes at least one of stress of the user, sleeping hours of the user, an exercise amount of the user, a dietary habit of the user, a smoking amount of the user, and alcohol drinking amount of the user; outputs the improvement target obtained by inputting the personal data to a trained model having a capability of outputting an improvement target for improving the complex disease state, as the improvement target to be achieved by the user; store individual disease definition information defining a correspondence relationship between the personal data and the disease state of the individual disease, and target definition information defining an improvement target when the combination of the disease states of the individual diseases or the combination of the disease state of the individual disease and the personal data is the complex disease state, determines the disease state of the user by referring to the individual disease definition information, acquires the improvement target when the combination of the disease states of the individual diseases or the combination of the disease state of the individual disease and the personal data is the complex disease state, by referring to the target definition information, and outputs the acquired improvement target as the improvement target to be achieved by the user; receive a behavior target to be handled by the user from the user, from a plurality of options relating to a behavior target for achieving the improvement target, outputs the behavior target to be handled by the user, which is received by a doctor who examines the user; determines the plurality of options, based on the personal data, the improvement target, or the complex disease state of the user; receives an input of an answer to questionnaire relating to the behavior target to be handled by the user, calculate a score relating to an achievement degree of the behavior target to be handled by the user, based on the answer to questionnaire received, and outputs the score; wherein the behavior target includes at least one of a behavior target relating to stress improvement of the user, a behavior target relating to improvement in sleeping hours of the user, a behavior target relating to exercise amount improvement of the user, a behavior target relating to improvement in dietary habits of the user, a behavior target relating to smoking amount reduction of the user, and a behavior target relating to alcohol drinking amount reduction of the user; calculates a risk for each examination item for the individual disease forming the complex disease by using a reference value of one or more examination items relating to the individual disease and examination data for the examination item obtained by examining the user, determines that the user is in the complex disease state, when the calculated risk for each examination item satisfies a predetermined condition, and output the improvement target to be achieved by the user to improve the complex disease state; wherein when the calculated risk for each examination item satisfies the predetermined condition, a value obtained by averaging the calculated risks for each examination item is equal to or greater than a predetermined threshold value, and outputs the value obtained by averaging the calculated risks for each examination item, as a value indicating a risk relating to the complex disease state. These are all just further describing the abstract idea recited in claim 1, without adding significantly more.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. In particular, the output unit, storage unit, first reception unit, and calculation unit are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions of setting data, storing data, outputting data, determining data, acquiring data, receiving data, and calculating data) such that it amounts no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible.
Step 2B:
Regarding Step 2B, independent claims 1, 14, and 15 do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for reasons the same as those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application.
Regarding the additional limitations directed to a computer/device/units acquiring and outputting data, all of which the Examiner submits merely add insignificant extra-solution activity to the abstract idea or are claimed in a merely generic manner (e.g., at a high level of generality), the Examiner further submits that such steps are not unconventional as they merely consist of receiving and transmitting data over a network. See MPEP 2106.05(d)(II).
The dependent claims do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the dependent claims do not integrate the at least one abstract idea into a practical application.
Therefore, claims 1-15 are ineligible under 35 USC §101.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “…unit configured to…” in claims 1, 7, 8, and 10.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Objections
Claims 1, 14, and 15 are objected to because of the following informalities: change “the disease states of the individual diseases“ to “ Appropriate correction is required.
Claims 1, 14, and 15 are objected to because of the following informalities: it is unclear if the “a complex disease state” is the same as the “a disease state of the user for an individual disease forming a complex disease” recited earlier in the claim, or if it is a different disease state. Appropriate correction is required.
Claims 6 and 7 are objected to because of the following informalities: it is unclear if the “an improvement target” is the same “an improvement target” recited in claim 1, or different. Appropriate correction is required.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 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.
Claim(s) 1-5, 7-11, 14, and 15 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Dias et al. (US 2018/0060494 A1).
(A) Referring to claim 1, Dias discloses A medical assistance device comprising (see Fig. 1 and para. 99 & 100 of Dias):
an acquisition unit configured to acquire personal data including at least one of examination data and medical interview data of a user (para. 39 & 136 of Dias; The patient health management system 410 may receive a request to generate a personalized patient care plan for a particular patient, such as from a physician's computing system, a patient computing system, or the like, which initiates the processes of the patient health management system 410 including retrieving information about the specified patient from the EMR sources 420. The EMR sources 420 provide patient demographic and medical data, gathered from questionnaires, electronic medical records, and the like, to the medical data analysis engine 412 which analyzes the received data and extracts the necessary data for generating patient care plan from the demographic and medical data received.); and
an output unit configured to determine a disease state of the user for an individual disease forming a complex disease, based on the personal data, and configured to output an improvement target to be achieved by the user to improve a complex disease state, when a combination of the disease states of the individual diseases or a combination of the disease state of the individual disease and the personal data is the complex disease state (para. 27, 39, 62, and 160 of Dias; collect patient demographic and medical data, such as from questionnaires, electronic medical records (EMRs), lab test results, hospital records, insurance company records, governmental agency reports, and the like, and generate a baseline patient care plan based on an initial diagnosis of the patient's medical condition, one or more categorizations of the patient based on the collected demographic and medical data, established patient care plan guidelines and knowledge, such as from official medical diagnosis and treatment guidelines and knowledge sources, and goals to be achieved by the patient care plan. Thus, for example, a patient's demographic information and electronic medical records may indicate that the patient is a 40 year old female that has been diagnosed with diabetes. Various pre-established categories and sub-categories may be defined for different types of patients in an ontology based on the various demographic and medical history characteristics, e.g., a category for diabetes patients, a sub-category of patients in the age range of 40 to 50 years old, a sub-sub-category of female patients, and so on.).
(B) Referring to claim 2, Dias discloses wherein the improvement target includes an improvement target value for an examination value included in the personal data (para. 58 and 148 of Dias).
(C) Referring to claim 3, Dias discloses wherein the output unit sets an improvement target for the examination value included in the personal data, based on the combination of the disease states of the individual diseases or the combination of the disease state of the individual disease and the personal data (para. 27, 39, 58, 62, 148 and 160 of Dias).
(D) Referring to claim 4, Dias discloses wherein the personal data includes data relating to a lifestyle habit of the user, and the improvement target includes an improvement target for the lifestyle habit of the user (para. 27, 34, 35, 38, 43, and 44 of Dias).
(E) Referring to claim 5, Dias discloses wherein the lifestyle habit includes at least one of stress of the user, sleeping hours of the user, an exercise amount of the user, a dietary habit of the user, a smoking amount of the user, and alcohol drinking amount of the user (para. 17 and 44 of Dias).
(F) Referring to claim 7, Dias discloses further comprising: a storage unit configured to store individual disease definition information defining a correspondence relationship between the personal data and the disease state of the individual disease, and target definition information defining an improvement target when the combination of the disease states of the individual diseases or the combination of the disease state of the individual disease and the personal data is the complex disease state, wherein the output unit determines the disease state of the user by referring to the individual disease definition information, acquires the improvement target when the combination of the disease states of the individual diseases or the combination of the disease state of the individual disease and the personal data is the complex disease state, by referring to the target definition information, and outputs the acquired improvement target as the improvement target to be achieved by the user (Fig. 1, para. 19, 22, and 128 of Dias).
(G) Referring to claim 8, Dias discloses further comprising: a first reception unit configured to receive a behavior target to be handled by the user from the user, from a plurality of options relating to a behavior target for achieving the improvement target, wherein the output unit outputs the behavior target to be handled by the user, which is received by the first reception unit, to a terminal used by a doctor who examines the user (Fig. 1, para. 30, 34, 48, 49, 63, and 128 of Dias).
(H) Referring to claim 9, Dias discloses wherein the first reception unit determines the plurality of options, based on the personal data, the improvement target, or the complex disease state of the user (para. 27-29 and 45-48 of Dias).
(I) Referring to claim 10, Dias discloses wherein the first reception unit receives an input of an answer to questionnaire relating to the behavior target to be handled by the user, the medical assistance device further comprises a calculation unit configured to calculate a score relating to an achievement degree of the behavior target to be handled by the user, based on the answer to questionnaire received by the first reception unit, and the output unit outputs the score calculated by the calculation unit (para. 35, 39, 40, 58, 125, 131, and 136 of Dias).
(J) Referring to claim 11, Dias discloses wherein the behavior target includes at least one of a behavior target relating to stress improvement of the user, a behavior target relating to improvement in sleeping hours of the user, a behavior target relating to exercise amount improvement of the user, a behavior target relating to improvement in dietary habits of the user, a behavior target relating to smoking amount reduction of the user, and a behavior target relating to alcohol drinking amount reduction of the user (para. 40 and 55-57 of Dias).
(K) Referring to claim 14, Dias discloses A medical assistance method executed by a medical assistance device, the method comprising (para. 1 of Dias; an improved data processing apparatus and method and more specifically to mechanisms for providing medical treatment recommendations for patients based on both the patient's electronic medical records and other exogenous information.):
a step of acquiring personal data including at least one of examination data and medical interview data of a user (para. 39 & 136 of Dias; The patient health management system 410 may receive a request to generate a personalized patient care plan for a particular patient, such as from a physician's computing system, a patient computing system, or the like, which initiates the processes of the patient health management system 410 including retrieving information about the specified patient from the EMR sources 420. The EMR sources 420 provide patient demographic and medical data, gathered from questionnaires, electronic medical records, and the like, to the medical data analysis engine 412 which analyzes the received data and extracts the necessary data for generating patient care plan from the demographic and medical data received.); and
a step of determining a disease state of the user for an individual disease forming a complex disease, based on the personal data, and outputting an improvement target to be achieved by the user to improve a complex disease state, when a combination of the disease states of the individual diseases or a combination of the disease state of the individual disease and the personal data is the complex disease state (para. 27, 39, 62, and 160 of Dias; collect patient demographic and medical data, such as from questionnaires, electronic medical records (EMRs), lab test results, hospital records, insurance company records, governmental agency reports, and the like, and generate a baseline patient care plan based on an initial diagnosis of the patient's medical condition, one or more categorizations of the patient based on the collected demographic and medical data, established patient care plan guidelines and knowledge, such as from official medical diagnosis and treatment guidelines and knowledge sources, and goals to be achieved by the patient care plan. Thus, for example, a patient's demographic information and electronic medical records may indicate that the patient is a 40 year old female that has been diagnosed with diabetes. Various pre-established categories and sub-categories may be defined for different types of patients in an ontology based on the various demographic and medical history characteristics, e.g., a category for diabetes patients, a sub-category of patients in the age range of 40 to 50 years old, a sub-sub-category of female patients, and so on.).
(L) Referring to claim 15, Dias discloses A computer-readable, non-transitory storage medium storing a medical assistance program causing a computer to execute a process comprising (abstract, para. 5, 23, and 66 of Dias; The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device.):
a step of acquiring personal data including at least one of examination data and medical interview data of a user (para. 39 & 136 of Dias; The patient health management system 410 may receive a request to generate a personalized patient care plan for a particular patient, such as from a physician's computing system, a patient computing system, or the like, which initiates the processes of the patient health management system 410 including retrieving information about the specified patient from the EMR sources 420. The EMR sources 420 provide patient demographic and medical data, gathered from questionnaires, electronic medical records, and the like, to the medical data analysis engine 412 which analyzes the received data and extracts the necessary data for generating patient care plan from the demographic and medical data received.); and
a step of determining a disease state of the user for an individual disease forming a complex disease, based on the personal data, and outputting an improvement target to be achieved by the user to improve a complex disease state, when a combination of the disease states of the individual diseases or a combination of the disease state of the individual disease and the personal data is the complex disease state (para. 27, 39, 62, and 160 of Dias; collect patient demographic and medical data, such as from questionnaires, electronic medical records (EMRs), lab test results, hospital records, insurance company records, governmental agency reports, and the like, and generate a baseline patient care plan based on an initial diagnosis of the patient's medical condition, one or more categorizations of the patient based on the collected demographic and medical data, established patient care plan guidelines and knowledge, such as from official medical diagnosis and treatment guidelines and knowledge sources, and goals to be achieved by the patient care plan. Thus, for example, a patient's demographic information and electronic medical records may indicate that the patient is a 40 year old female that has been diagnosed with diabetes. Various pre-established categories and sub-categories may be defined for different types of patients in an ontology based on the various demographic and medical history characteristics, e.g., a category for diabetes patients, a sub-category of patients in the age range of 40 to 50 years old, a sub-sub-category of female patients, and so on.).
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) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dias et al. (US 2018/0060494 A1) in view of Anushiravani et al. (US 2020/0152330 A1).
(A) Referring to claim 6, Dias does not disclose wherein the output unit outputs the improvement target obtained by inputting the personal data to a trained model having a capability of outputting an improvement target for improving the complex disease state, as the improvement target to be achieved by the user.
Anushiravani discloses wherein the output unit outputs the improvement target obtained by inputting the personal data to a trained model having a capability of outputting an improvement target for improving the complex disease state, as the improvement target to be achieved by the user (para. 82, 83, 95, and 126 of Anushiravani).
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to combine the aforementioned features of Anushiravani within Dias. The motivation for doing so would have been to predict effective treatment (para. 82 of Anushiravani).
Claim(s) 12 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dias et al. (US 2018/0060494 A1) in view of Sweeney et al. (US 2014/0343439 A1).
(A) Referring to claim 12, Dias does not disclose wherein the output unit calculates a risk for each examination item for the individual disease forming the complex disease by using a reference value of one or more examination items relating to the individual disease and examination data for the examination item obtained by examining the user, determines that the user is in the complex disease state, when the calculated risk for each examination item satisfies a predetermined condition, and output the improvement target to be achieved by the user to improve the complex disease state.
Sweeney discloses wherein the output unit calculates a risk for each examination item for the individual disease forming the complex disease by using a reference value of one or more examination items relating to the individual disease and examination data for the examination item obtained by examining the user, determines that the user is in the complex disease state, when the calculated risk for each examination item satisfies a predetermined condition, and output the improvement target to be achieved by the user to improve the complex disease state (para. 78-81 of Sweeney).
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to combine the aforementioned features of Sweeney within Dias. The motivation for doing so would have been to determine recommendations for intervention, further testing, or treatment options for the patient (para. 80 of Sweeney).
(B) Referring to claim 13, Dias does not disclose wherein when the calculated risk for each examination item satisfies the predetermined condition, a value obtained by averaging the calculated risks for each examination item is equal to or greater than a predetermined threshold value, and the output unit outputs the value obtained by averaging the calculated risks for each examination item, as a value indicating a risk relating to the complex disease state.
Sweeney discloses wherein when the calculated risk for each examination item satisfies the predetermined condition, a value obtained by averaging the calculated risks for each examination item is equal to or greater than a predetermined threshold value, and the output unit outputs the value obtained by averaging the calculated risks for each examination item, as a value indicating a risk relating to the complex disease state (para. 78-81, 34, 59, and 66 of Sweeney).
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to combine the aforementioned features of Sweeney within Dias. The motivation for doing so would have been to determine recommendations for intervention, further testing, or treatment options for the patient (para. 80 of Sweeney).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The cited but not applied prior art teaches personalized health risk assessment for critical care (US 2012/0059779 A1) and identifying and ranking individual-level risk factors using personalized predictive models (US 2016/0283686 A1).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LENA NAJARIAN whose telephone number is (571)272-7072. The examiner can normally be reached Monday - Friday 9:30 am-6 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mamon Obeid can be reached at (571)270-1813. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/LENA NAJARIAN/Primary Examiner, Art Unit 3687
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