DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of claims
The claim set received 22 July 2026 has been entered.
Claims 1-5 and 8 are amended.
Claims 6-7, 9, and 11 are previously cancelled.
Claim 10 is cancelled.
Claims 1-5 and 8 are pending.
Priority
This application is a 371 of PCT/JP2020014901 filed 31 March 2020.
Specification
The objection to the specification in the Office Action mailed 23 April 2026 is withdrawn in view of the amendments to the specification received 22 July 2026.
The amended specification received on 22 July 2026 has been entered into the application.
Claim Rejections - 35 USC § 112
35 USC § 112(a)
The rejection of claim 1 under 35 U.S.C. 112(a) in the Office Action mailed 23 April 2026 is withdrawn in view of the amendments field 22 July 2026.
35 USC § 112(b)
The rejection of claim 1-5 under 35 U.S.C. 112(b) in the Office Action mailed 23 April 2026 is withdrawn in view of the amendments field 22 July 2026.
The rejection of claim 10 under 35 U.S.C. 112(b) in the Office Action mailed 23 April 2026 is withdrawn in view of the amendments field 22 July 2026 because claim 10 was cancelled.
The rejection of claim 4 under 35 U.S.C. 112(b) in the Office Action mailed 23 April 2026 is withdrawn in view of the amendments field 22 July 2026 because claim 10 was cancelled.
Claim Rejections - 35 USC § 101
The instant rejection is maintained for reason for record in the Office Action mailed 23 April 2026 and modified in view of the amendments filed 22 July 2026. It is noted the amendments received 22 July 206 are necessitated by new ground(s) of rejection.
The rejection of claim 10 under 35 U.S.C. 101 in the Office Action mailed 23 April 2026 is withdrawn in view of the amendments field 22 July 2026 because claim 10 was cancelled.
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 1-5 and 8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Step I - Process, Machine, Manufacture or Composition
Claims 1-5 are drawn to a device, so a machine.
Claim 8 is drawn to a method, so a process.
Step 2A Prong I - Identification of an Abstract Idea
Claim 1 recites a device while claim 8 recites a method for determining a clinical examination item for each user. Claims 1 and 8 recite similar limitations and are therefore examined similarly.
Claims 1 and 8 recite:
estimate, based on genetic factors of the user and nongenetic factors based on behaviors or habits of the user, a disease that the user develops with high possibility
This step can be performed in the human mind by organizing information (i.e., behavior habit based genetic factors) to estimate the possibility of a user developing a disease and is therefore an abstract idea. This step encompasses performing mathematical/statistical computations (i.e., high possibility, estimations) for estimating a probability which reads on abstract ideas. Here, the term “estimating” is interpretated as an alternative term for “calculating”. See MPEP 2106.04(a)(2)(I)(C).
determine, for the user, as an individual examination item, an examination item for detecting presence or absence of the estimated disease
This step can be performed in the human mind by observing and evaluating information (i.e., individual examination and examination item) for detecting the estimated disease and is therefore an abstract.
determine an examination item for detecting a disease having a high incidence rate in a first organization to which the user belongs or a disease having a high incidence rate in common in the first organization and a second organization having an attribute similar to an attribute of the first organization as a common examination item of people belonging to the first or second organization.
This step can be performed in the human by following instructions to determine an examination item for detecting a disease and is therefore an abstract idea.
wherein the common examination item is selected based on a ratio of an incidence rate of a disease in the first or second organization to a general incidence rate of the disease
This step can be performed in the human mind by observing and evaluating information (i.e., a ratio of an incidence rate of a disease in the first or second organization) to select data (i.e., examination item) and is therefore an abstract idea.
determine an examination item of the user based on the individual examination item and the common examination item
This step can be performed in the human mind by observing and evaluating information (i.e., the individual examination item and the common examination item) to determine an examination item and is therefore an abstract idea.
Claims 2-5 are further drawn to limitations that describe the abstract ideas of claim 1 and are therefore also abstract ideas.
Step 2A Prong II - Consideration of Practical Application
Claim 1 and 8 do not recite any additional elements which integrate the recited judicial exception into a practical application. Here, in the instant case, the claims merely set forth a method of data analysis for determining an examination item of the user based on information (i.e., individual examination item and the common examination item). As such, practicing the claims merely results in determining an examination item. Such a result only produces information and does not provide for a practical application in the physical-realm of physical things and acts, i.e., the claims do not utilize the data generated by the judicial exception to affect any type of change. See MPEP 2106.04(a)(2)(A)(iv). Thus, because a judicial exception of the claims, alone, is not eligible subject matter and the claims do not encompass any additional elements other than tangential computer elements, the claims do not construct a practical application and/or improvement to technology as enumerated below. See MPEP 2106.04(d). Therefore, the claims, under Step 2A Prong II of the 101 analyses, are not patent ineligible.
Claim 4 recites “…the examination item determiner estimates using, based a machine learning model generated by a method of machine learning”. Here, even though the claimed step recites an estimation indicating a relationship between factors and disease incidence based on a learned model generated by a method of machine learning model, the machine learning model is broadly and generically recited and reads on mere instructions to implement an abstract idea on a generic computer and reads on mathematical/statistical computations (i.e., neural network [Spec 0052]). See 2024 Subject Matter Eligibility Update (AI) [Example 47 Claim 2] and MPEP 2106.04(a)(2)(III)(C)(1-3).
Furthermore and for sake of compact prosecution, even if the machine learning model is also considered an additional element, the machine learning method (MLM) is used to generally apply the abstract idea without limiting how the trained (MLM) functions. The MLM is described at a high level such that it amounts to using a computer with a generic MLM to apply the abstract idea. These limitations only recite the outcomes for “estimating a relationship between human non-genetic factors and incidence rates and non-genetic factors and incidence rates of the user” without any details about how the estimations are determined using a method of machine learning which does not integrate the judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". See 2024 Subject Matter Eligibility Update (AI) [Example 47 Claim 2] and MPEP 2106.05(f).
This judicial exception is not integrated into a practical application because the claims do not meet any of the following criteria:
An additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses 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 more than a drafting effort designed to monopolize the exception.
Step 2B - Consideration of Additional Elements and Significantly More
The claimed method also recites "additional elements" that are not limitations drawn to an abstract idea.
The recited additional element of using computer device of claim 1 and the non-transitory computer readable media of claim 10 does not recite significantly more than the recited judicial exception because using a computer (i.e., device) to process an abstract idea is merely tangential to the claimed method. Furthermore, using computer elements to store data and computer instructions (i.e., computer software) is tangential to the claimed steps and is deemed well-known and conventional. See MPEP 2106.05(b), 2106.05(d), and 2106.05(g).
In conclusion, and when viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea recited in the instantly presented claims into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Response to Arguments
The Applicant's arguments filed 22 July 2026 have been fully considered but they are not persuasive.
The Applicant states the claims are drawn to an improvement to technology. The Applicant points to the MPEP 2106.04(d)(I) for guidance. The Applicant states the claims set forth improved technique for identifying diseases that are atypically prevalent within that specific organizational environment. The points to the specification paragraph [0002-0011] for guidance [remarks, page 7]. The Applicant states the present invention provides a practical application by functioning as an advanced, customized clinical examination system that identifies a disease having a high incidence rate "in a first organization to which the user belongs" [remarks, page 7-8]. The Applicant states the present application provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The Applicant points to the MPEP 2106.05(a) for guidance. The Applicant points to the MPEP 2106.05(a) for guidance. The Applicant states the claimed invention specifically determines common examination items by calculating a ratio of the disease incidence rate within a specific organization (e.g., a specific company to which the user belongs) to the general incidence rate of the disease in the broader population. The Applicant states this provides a particular solution to achieve a desired outcome [remarks, page 8]. The Applicant states the combination of claimed elements set forth an improved technique for identifying diseases that are atypically prevalent within that specific organizational environment (e.g., due to specific occupational hazards or lifestyle patterns common to that workplace) and thereby is integrated into a practical application [remarks, page 8].
In response, the argument is not persuasive because claims 1 and 8 are drawn to abstract ideas without any additional element to integrate the judicial exception into a practical application/improvement to technology. As noted in Step 2A Prong II of the 101 analyses above, claims 1 and 8 are drawn to data analysis (i.e., judicial exception) alone without any additional elements (i.e., other than tangential computer elements) to integrate the judicial exception which is insufficient to provide a practical application or improvement to technology. The argument is not further persuasive because determining/calculating an incidence rate (i.e., ratio) reads on abstract idea, more particularly, mathematical concepts. Here, the abstract ideas are not integrated with any additional elements such that to provide an improvement or a practical application, and calculating a ratio encompasses performing mathematical computations which reads on abstract ideas. Thus, because a judicial exception of the claims, alone, is not eligible subject matter and the claims do not encompass any additional elements other than tangential computer elements, the claims do not construct a practical application and/or improvement to technology. See MPEP 2106.04(d). Therefore, the claims, under Step 2A Prong II of the 101 analyses, are not patent ineligible.
Claim Rejections - 35 USC § 103
The instant rejection is maintained for reason for record in the Office Action mailed 23 April 2026 and modified in view of the amendments filed 22 July 2026. It is noted the amendments received 22 July 206 are necessitated by new ground(s) of rejection.
The rejection of claim(s) 10 under 35 U.S.C. 103 as being unpatentable over Park et al. (US Patent Pub: US 2019/0172587, Patent Pub Date: 06 June 2019) in view of Iribarren et al. (Epidemiology and infection, 1998-10, Vol.121 (2), p.335-347) in the Office Action mailed 23 April 2026 is withdrawn in view of the amendments field 22 July 2026 because claim 10 was cancelled.
The rejection of claim(s) 5 under 35 U.S.C. 103 as being unpatentable over Park in view of Iribarren, as applied to claims 1-4, 8, and 10, and in further view of Perkins (US Patent Application: US 2018/0320233, Patent Pub Date: 08 November 2018) in the Office Action mailed 23 April 2026 is withdrawn in view of the amendments field 22 July 2026 because claim 10 was cancelled.
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 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-4 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Park et al. (US Patent Pub: US 2019/0172587, Patent Pub Date: 06 June 2019) in view of Iribarren et al. (Epidemiology and infection, 1998-10, Vol.121 (2), p.335-347).
Claim 1 recites a device while claim 8 recites a method for determining a clinical examination item for each user. Claims 1 and 8 recite similar limitations and are therefore examined similarly.
Claim 1 recites estimate, based on genetic factors of the user and nongenetic factors based on behaviors or habits of the user, a disease that the user develops with high possibility. Claim 1 recites determining, for the user, as an individual examination item, an examination item for detecting presence or absence of the estimated disease.
Claim 1 recites determine an examination item for detecting a disease having a high incidence rate in a first organization to which the user belongs or a disease having a high incidence rate in common in the first organization and a second organization having an attribute similar to an attribute of the first organization as a common examination item of people belonging to the first or second organization.
Claim 1 recites wherein the common examination item is selected based on a ratio of an incidence rate of a disease in the first or second organization to a general incidence rate of the disease.
Claim 1 recites determine an examination item of the user based on the individual examination item and the common examination item.
Park
Park et al. (Park) discloses providing an incidence by repeating analysis and estimation [Park, figure 4]. Park discloses a statistical probability model that probabilistically represent the disease risk based on state variables (i.e., marriage state, gender, exposure to smoking, etc., [ Park, claims 11-13]) and genetic information [Park, claim 1], as in instant claim 1 estimating, based on genetic factors of the user and nongenetic factors based on behaviors or habits of the user, a disease that the user develops with high possibility.
Park discloses using probabilities [ Park, figures 5-6], incidence [Park, figure 4], and disease risk factor [Park, figure 6] (i.e., an examination item) for predicting disease risk of metabolic disorder [Park, claim 1], as instant in instant claim 1 determining, for the user, as an individual examination item, an examination item for detecting presence or absence of the estimated disease.
Park discloses the method can be applied to health care field of general populations in the community or can be used on selected high-risk groups in the clinical setting [Park, page 3 right para 0035]. Park discloses incidence [Park, fig 4]. Park discloses incidence rates of HTN [fig 9A], obesity [9H], and metabolic syndrome [9L]. Park discloses using disease risks (i.e., examination item) [Park, claim 1], as in instant claim 1 determining an examination item for detecting a disease having a high incidence rate in a first organization to which the user belongs. Therefore, it would be obvious to use any clinical setting or any entity (i.e., hospital, clinic) studying general populations with respect to incidence rates of a diseases found in organizations (i.e., clinic, hospital, emergency room) from which patient data is used or derived.
Park discloses using r(t) =
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[Park, page 15 col 0157-0158]. Park discloses a disease predicting implements using a ratio of incidences [Park, page 15 col 0158]. Park discloses using probabilities [Park, figures 5-6], incidence [Park, figure 4], and disease risk factor [Park, figure 6] (i.e., an examination item) for predicting disease risk of metabolic disorder [Park, claim 1]. Park discloses with the present invention, it is possible to confirm a current possible disease probability of a metabolic disorder such as hyper-tension, diabetes, obesity, and metabolic syndrome, based on individual's state variables and genetic information confirm which group of four risk groups (low, normal, high, very high) current states of subjects who are not yet diagnosed with the disease belong, and predict a future incidence probability of hypertension, diabetes, obesity, or metabolic syndrome based on that to prevent and treat the disease through early diagnosis [Park, page 3 right col para 0031], as in instant claim 1 where the common examination item is selected based on a ratio of an incidence rate of a disease in the first or second organization to a general incidence rate of the disease. Here, because Park discloses their invention can predict future incidence risk probabilities of metabolic disorders such as hypertension, diabetes, obesity, and metabolic syndromes (i.e., examination items) using the incidence ratio of equation 14 [Park, page 15 left col 0157], it is obvious the system/method/algorithm of Park utilizes said incidence ratio for determining/predicting/selecting the health status(es) (i.e., examination items) of a subject(s) for outputting current disease and/or future disease risks
Park discloses using different populations/cohorts from big data collection centers with data from 21,000 and 10,000 people and using common data such as past history, lifestyle, and eating habits of users in the populations for determining disease risks and Korean health index [figures 5-6], as in instant claim 1 recites determining an examination item of the user based on the individual examination item and the common examination item.
Dependent claim(s): 2-4
Park discloses using lifestyle and eating habit data [figure 6], as in instant claim 2.
Park discloses a workflow using a statistical and machine learning algorithms using lifestyle data and genetic data to produce incidences [Park, fig 4]. Park discloses using a weight statistical probability model [Park, claim 1]. Park discloses using a degree of relationships may be obtained by calcualting a weight sum of information into an input layer [Park, page 6 left col para 0065]. Park discloses a disease risk for predicting a subjects disease risks [Park, claim 1]. Park discloses different risk factors associated with HTN [fig 9A], obesity [fig 9H], and metabolic syndrome [fig 9L] and discloses using gene data [Park, fig 6], as in instant claim 3. Thus, it is obvious the genetic and non-genetic factors are weighted and summed together to predict disease (i.e., HTN, metabolic disorder) because Park discloses the contribution of each risk factor individual metabolic syndrome incidence is combined to produce an overall incidence in an individual’s metabolic syndrome.
Park discloses a machine learning model that generates a machine learning model that analyzes a degree of a relationship between at least one of a plurality of state variables (i.e., non-genetic factors) and genetic information (i.e., genetic factors) and a disease risk of metabolic disorders with the plurality of state variables including a living condition variable and a health condition variable of a patient with a metabolic disorder, generic information, and the disease risk of the metabolic disorder as inputs [Park, claim 1], as in claim 4.
Park does not teach
Park does not teach claim 1 a disease having a high incidence rate in common in the first organization and a second organization having an attribute similar to an attribute of the first organization as a common examination item of people belonging to the first or second organization.
Iribarren
Iribarren et al. (Iribarren) teach using a multiethnic cohort of adult members of the Kaiser Permanente Medical Care Program between total cholesterol and risk of infections [Summary]. Irribarren teaches the incidence rates from cohorts are associated with Kaiser Permanente Center (i.e., second organization) [Irribarren, page 336 left col cohort description]. Irribarren teaches performing analysis of four strata of personal history of other diseases such as thyroid disease (i.e., metabolic disease) [Irribarren, page 338 left col last para and page 341 table 3]. Iribarren teaches using total cholesterol for analyzing in-hospital disease incidence rates (i.e., attribute) [page 340 table 2]. Park discloses using Korean genome epidemiology baseline and gene data which was obtained from Ansan-Anseong Cohort which is part of the Korean Genome and Epidemiology study performed by the Korea Centers for Disease control (i.e., first organization) [Park, page 1 right col para 009]. Park discloses different risk factors associated with metabolic syndrome [fig 9L] (i.e., thyroid disease [Park, claim 12]). Park discloses using gene data [Park, fig 6]. Park discloses using a total cholesterol (i.e., similar attribute) [Park, tables 5 and 6]. Park discloses an incidence risk optimal prediction value [Park, fig 4], as in claim 1 a disease having a high incidence rate in common in the first organization and a second organization having an attribute similar to an attribute of the first organization as a common examination item of people belonging to the first or second organization. Here, because Park discloses a first organization (i.e., Korea Centers for Disease control) and Irribarren teaches a second organization (i.e., Kaiser Permanente Medical Care Program) that Park does not disclose and because Park and Irribarren both use total cholesterol values with respect to disease (i.e., metabolic/thyroid) incidence rates, it would be obvious to combine these limitations of Park and Irribarren to teach two organizations having similar incidence rates for a disease (i.e., metabolic/thyroid) based on similar or common attributes (i.e., total cholesterol) and/or other factors.
It would be obvious to one of ordinary skill in the art by the effective filing date of the claimed invention to modify Park in view of Iribarren because Iribarren analyzes cholesterol levels with respect to incidence of disease requiring hospitalization or an infection acquired in a hospital (i.e., nosocomial). One of ordinary skill in the art would be motivated to combine Park in view of Iribarren because Iribarren teaches analyzing populations of patients from the Kaiser Permanent Medical Center (i.e., organization) having diseases such as intestinal, viral, kidney, venereal, for example [Iribarren, page 341 table 3]. Here, one of ordinary skill in the art would have a reasonable expectation success combining Park in view of Iribarren because Park discloses a method that can be applied to healthcare setting populations and/or can be used on selected high-risk groups in the clinical setting [Park, page 3 right para 0035] while Iribarren teaches disease related incidences using data from a pre-paid medical health from Kaiser Permanente Medical Center. Thus, because Park discloses a method that can be applied to populations in the community or can be used on selected high-risk groups in the clinical setting it would be obvious to use the method of Park to analyze the medical center data of Iribarren to determine a disease risk. Therefore, combining the genetic and non-genetic data analysis of Park for predicting disease risks with the Kaiser Permanente Medical Center data of Iribarren would yield a predictable result using gene data and non-genetic data (i.e., lifestyle, smoking, alcohol) for determining examination items of a user.
Claim(s) 5 is rejected under 35 U.S.C. 103 as being unpatentable over Park in view of Iribarren, as applied to claims 1-4 and 8, and in further view of Perkins (US Patent Application: US 2018/0320233, Patent Pub Date: 08 November 2018).
Park in view of Iribarren teach claims 1-4 and 8.
Park in view of Iribarren teach a method for determining an examination item using non-genetic data (i.e., lifestyle, smoking) and genetic data (i.e., gene data).
Park in view of Iribarren does not teach claims 5.
Perkins discloses using responses form NHANES, a U.S population-based cohort [Perkins, page 21 right col para 0073]. Perkin discloses using standard incidence ratio’s and comparing study participants characteristics and NHANES cohort data regarding Alzheimer’s and alcohol use, smoking, for exmaple [Perkins pages 9-10 table 1], as in claim 5. Thus, it would be obvious to use alcohol and/or Alzheimer’s disease (i.e., examination items) from a cohort study and NHANES study for selecting examination items using an incidence rate
It would be obvious to one of ordinary skill in the art by the effective filing date of the claimed invention to modify Park in view of Iribarren and in further view of Perkins because Perkins discloses utilizing a standardized incidence ratio using such items as sex, LDL, alcohol use, and smoking [Perkins, table 1]. One of ordinary skill in the art would be motivated to combine Park in view of Irribarren and in further view of Perkins because Perkins discloses using confidence scores from genetic risk rule and non-genetic risk rule data for detecting undiagnosed medical condition [Perkins, claim 1]. Thus, one of ordinary skill in the art would have a reasonable expectation success combining Park in view of Irribarren and in further view of Perkins because Perkins also teaches data analysis method using genetic rules and non-genetic rules, and Perkins discloses using a standardized incidences to provide relationships between different factors such as diabetes and cirrhosis and smoking and HDL, for example. Therefore, combining Park in view of Irribarren and in further view of Perkins would yield a predictable method step for analyzing population data from multiple sources (i.e., clinical settings, hospitals) for selecting an examination item based on a ratio of an incidence rate of a disease between sample populations.
Response to Arguments
The Applicant's arguments filed 22 July 2026 have been fully considered but they are not persuasive.
The Applicant points the amendments to claim 1 for guidance. The Applicant states none of the cited references teaches or disclose the “ratio” feature [remarks, page 9]. The Applicant points to Park paragraphs [0119-0133]. The Applicant states Park does not teach identifying common examination items based on comparing an incidence rate in a user's specific organization to a general incidence rate [remarks, page 9]. The Applicant points to Iribarren.
The Applicant states Iribarren fails to teach or suggest using a ratio between a specific organization's incidence rate and a general incidence rate to dynamically select clinical examination items [remarks, page 10].
The Applicant points to Perkins reference. The Applicant states Perkins fails to teach or suggest utilizing the ratio of an organization specific incidence rate to a general incidence rate in order to extract common examination items uniquely required for the people belonging to that specific organization [remarks, page 10].
The Applicant points to the specification [0047] for guidance. The Applicant states “One of ordinary skill in the art would not be motivated to arrive at the claimed invention based on the combination of Park, Iribarren, and Perkins. Since Perkins only uses ratios to assess individual risks against a general cohort, and Park and Iribarren similarly focus on predicting risks based on generic factors or analyzing a single health plan cohort, there is no teaching, suggestion, or motivation in the cited art to calculate an organization-to-general-population incidence ratio for the purpose of determining common examination items for an organizational group.” [remarks, page 11].
In response, and as noted above in the 35 U.S.C § 103 rejection regarding the amended limitation of claim 1, Park discloses using r(t) =
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[Park, page 15 col 0157-0158]. Park discloses a disease predicting that uses ratio’s of incidences [Park, page 15 col 0158]. Park discloses using probabilities [Park, figures 5-6], incidence [Park, figure 4], and disease risk factor [Park, figure 6] for predicting disease risk of metabolic disorder [Park, claim 1]. Park discloses with the present invention, it is possible to confirm a current possible disease probability of a metabolic disorder such as hyper-tension, diabetes, obesity, and metabolic syndrome, based on individual's state variables and genetic information confirm which group of four risk groups (low, normal, high, very high) current states of subjects who are not yet diagnosed with the disease belong, and predict a future incidence probability of hypertension, diabetes, obesity, or metabolic syndrome based on that to prevent and treat the disease through early diagnosis [Park, page 3 right col para 0031].
Here, because Park discloses their invention can predict future incidence risk probabilities of metabolic disorders such as hypertension, diabetes, obesity, and metabolic syndromes (i.e., examination items) using the incidence ratio of equation 14 [Park, page 15 left col 0157] and the invention of Park requires using the equation 14 for predicting disease probabilities for diseases (i.e., metabolic syndrome), it is obvious the system/method of Park utilizes the incidence ratio of equation 14 for determining the health status of a subject for outputting current disease and future disease risks (i.e., examination items) [Park, figure 5] that have been selected/determined by their algorithm based on multiple genetic and non-genetic of said patient(s).
Thus, Park discloses the amended limitations of claims 1 and 8.
Therefore, the above 35 U.S.C § 103 rejection is maintained.
Conclusion
Claims 1-5 and 8 are rejected.
No claims are allowed.
Finality
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Inquiries
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOSEPH C PULLIAM whose telephone number is (571)272-8696. The examiner can normally be reached 0730-1700 M-F.
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/J.C.P./ Examiner, Art Unit 1687
/Anna Skibinsky/
Primary Examiner, AU 1635
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