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 .
Formal Matters
Applicant’s response, filed 1/30/2026, has been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Status of Claims
Claims 1-3 and 5-16 are currently pending and have been examined.
Claims 1-3 and 5-11 have been amended.
Claim 4 has been canceled.
Claims 12-16 are new.
Claims 1-3 and 5-16 have been rejected.
Information Disclosure Statement
The information disclosure statements (IDS) were submitted on 10/15/2025 and 6/20/2025. Both of the submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Priority
Acknowledgment is made of applicant's claim for foreign priority based on an application filed in Japan on 10/27/2023. The Examiner notes that the Priority Documents electronically retrieved by USPTO from a participating IP Office filed on 12/03/2025 are accepted and the application now receives the priority date of 10/27/2023.
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) are:
Claim 9 discloses, “the display control unit”
Because this/these claim limitation(s) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
Claim 9 discloses, “the display control unit”
Para 30 of the Applicant’s specification discloses, “as illustrated in Fig. 2, the processor 34 exhibits the functions of a medical information processing unit 36, an analysis unit 38, a comprehensive determination unit 40, and a display control unit 42 according to the medical determination support program stored in the memory 22. The processor 34 exhibits the above-mentioned functions to determine the state of the determination target part of the subject, which will be described in detail below.” Para 74 discloses, “The display control unit 42 performs a process of displaying the processing result of the medical determination support apparatus 16 on the display unit. For example, the display control unit 42 displays the processing result of the medical determination support apparatus 16 on the display of the user terminal 14.” Therefore, the specification provides proper support for the display control unit.
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 Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 9 and 15 are further rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 9 recites the limitation “the display control unit”. There is insufficient antecedent basis for this limitation in the claim.
Further, Claim 15 discloses, “… including the sensor is any one of a blood tester, a genetic tester, or an electro electrocardiogram a cardiac catheter examination apparatus.” The claim is indefinite because the placement of “or” indicates that “an electro electrocardiogram a cardiac catheter examination apparatus” is one option as a sensor. The Applicant’s specification at Para 22 discloses, “a blood tester, a genetic tester, an electrocardiograph, and a cardiac catheter examination apparatus.” Thus, the Examiner is interpreting claim 15 to read as, “… including the sensor is any one of a blood tester, a genetic tester, an electrocardiograph, or a cardiac catheter examination apparatus.”
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 1-3 and 5-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claimed invention is directed to an abstract idea without significantly more. Claims 1-3 and 5-16 are directed to a system, method, or product which are one of the statutory categories of invention. (Step 1: YES).
Independent Claim 1 discloses a medical determination support apparatus comprising: a processor, configured to: acquire a plurality of types of medical information related to an examination target part of a subject, wherein the plurality of types of medical information comprises any two of a medical image of the examination target part captured by a medical imaging apparatus, biological measurements of the examination target part measured by a medical measurement apparatus including a sensor, and a diagnostic result of the examination target part extracted from an electronic medical record; specify a current analysis item related to a predetermined medical disease on the examination target part to perform determination on a state of the examination target part on the basis of the plurality of types of medical information; analyze the plurality of types of medical information using a calculator group corresponding to each of the types of medical information, each of calculators included in the calculator group outputting partial analysis information for calculating an analysis result; calculate the analysis result with respect to the current analysis item related to the predetermined medical disease on the basis of a combination of the partial analysis information output by each of the calculators
Independent Claim 11 discloses the non-transitory computer-readable storage medium storing a medical determination support program causing a computer to perform the method as performed by claim 1.
Independent Claim 16 discloses the method as performed by the processor of the apparatus of claim 1.
The examiner is interpreting the above bolded limitations as additional elements as further discussed below. The remaining un-bolded limitations are merely directed to determining an analysis result for a subject based on medical information. The series of steps recited above describe managing personal behavior or relationships or interactions between people and thus are grouped as certain methods of organizing human activity which is an abstract idea. (Step 2A- Prong 1: YES. The claims are abstract).
This judicial exception is not integrated into a practical application. Limitations that are not indicative of integration into a practical application include: (1) Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05.f), (2) Adding insignificant extra- solution activity to the judicial exception (MPEP 2106.05.g), (3) Generally linking the use of the judicial exception to a particular technological environment or field of use (MPEP 2106.05.h).
Independent Claim 1 discloses the following additional elements:
A processor
a medical imaging apparatus
a medical measurement apparatus including a sensor
an electronic medical record
Independent Claim 11 discloses the following additional elements:
A non-transitory computer-readable storage medium storing a medical determination support program causing a computer to [perform the method]
a medical imaging apparatus
a medical measurement apparatus including a sensor
an electronic medical record
Independent Claim 16 discloses the following additional elements:
a medical measurement apparatus including a sensor
an electronic medical record
In particular, the processor (of claim 1), the medical imaging apparatus, the medical measurement apparatus including a sensor and the electronic medical record (of claims 1, 11, and 16), and the non-transitory computer-readable storage medium storing a medical determination support program causing a computer to [perform the method] (of claim 11) are recited at a high-level of generality such that it amounts to no more than mere instructions to implement an abstract idea by adding the words ‘apply it’ (or an equivalent) with the judicial exception.
Accordingly, claim(s) 1 and 11 are directed to an abstract idea(s) without a practical application. (Step 2A-Prong 2: NO: the additional claimed elements are not integrated into a practical application).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of the processor (of claim 1), the medical imaging apparatus, the medical measurement apparatus including a sensor and the electronic medical record (of claims 1, 11, and 16), and the non-transitory computer-readable storage medium storing a medical determination support program causing a computer to [perform the method] (of claim 11) amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept ("significantly more’). MPEP2106.05(I)(A) indicates that merely saying "apply it” or equivalent to the abstract idea cannot provide an inventive concept ("significantly more").
Accordingly, these additional elements, even in combination, do not provide significantly more. As such the independent claims 1 and 11 are not patent eligible. (Step 2B: NO. The claims do not provide significantly more).
Dependent claim(s) 2-10 are similarly rejected because they either further define/narrow the abstract idea and/or do not further limit the claim to a practical application or provide an inventive concept such that the claims are subject matter eligible even when considered individually or as an ordered combination. Dependent claims 6-10 do further disclose the additional element(s) of a comprehensive determination learning model (of claim 6) and a display unit (of claims 8-9), a display control unit (of claim 9), wherein each of the calculators could be a learning model (of claim 13), wherein the medical imaging apparatus is any one of an ultrasound diagnostic apparatus, an X-ray CT apparatus, a magnetic resonance imaging (MRI) apparatus, or a nuclear medicine examination apparatus (of claim 14), wherein the medical measurement apparatus including the sensor is any one of a blood tester, a genetic tester, or an electro electrocardiogram a cardiac catheter examination apparatus (of claim 15).
In particular, the comprehensive determination learning model (of claim 6), display unit (of claims 8-9), the display control unit (of claim 9), and wherein each of the calculators could be a learning model (of claim 13) are recited at a high-level of generality such that it amounts to no more than mere instructions to implement an abstract idea by adding the words ‘apply it’ (or an equivalent) with the judicial exception. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Claims 14-15 further disclose wherein the medical imaging apparatus is any one of an ultrasound diagnostic apparatus, an X-ray CT apparatus, a magnetic resonance imaging (MRI) apparatus, or a nuclear medicine examination apparatus (of claim 14), wherein the medical measurement apparatus including the sensor is any one of a blood tester, a genetic tester, or an electro electrocardiogram a cardiac catheter examination apparatus (of claim 15). These additional elements merely generally link the abstract idea to a particular technological environment or field of use. MPEP 2106.04(d)(1) indicates that generally linking an abstract idea to a particular technological environment or field of use cannot provide a practical application. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of the comprehensive determination learning model (of claim 6), display unit (of claims 8-9), the display control unit (of claim 9), and wherein each of the calculators could be a learning model (of claim 13) amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept ("significantly more’). MPEP2106.05(I)(A) indicates that merely saying "apply it” or equivalent to the abstract idea cannot provide an inventive concept ("significantly more").
Also, as discussed above with respect to integration of the abstract idea into a practical application, the additional elements wherein the medical imaging apparatus is any one of an ultrasound diagnostic apparatus, an X-ray CT apparatus, a magnetic resonance imaging (MRI) apparatus, or a nuclear medicine examination apparatus (of claim 14) and wherein the medical measurement apparatus including the sensor is any one of a blood tester, a genetic tester, or an electro electrocardiogram a cardiac catheter examination apparatus (of claim 15) were considered to generally link the abstract idea to a particular technological environment or field of use. This has been re-evaluated under the ‘significantly more’ analysis and has been found insufficient to provide significantly more. MPEP2106.05(I)(A) indicates that generally linking an abstract idea to a particular technological environment or field of use cannot provide an inventive concept (‘significantly more"). Accordingly, even in combination, these additional element do not provide significantly more.
Therefore, the dependent claims are also directed to an abstract idea.
Thus, Claims 1-3 and 5-16 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
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.
Claim(s) 1 and 13-16 are rejected under 35 U.S.C. 103 as being unpatentable over Amemiya (US PG Pub 2020/0380676 A1) in view of Kwon (KR 2021/0102102 A).
Regarding Claim 1, Amemiya discloses:
A medical determination support apparatus comprising: a processor, configured to: (See Para 31, disclosing a computer 20 that includes a CPU and a memory…)
acquire a plurality of types of medical information related to an examination target part of a subject, wherein the plurality of types of medical information comprises [any two of] a medical image of the examination target part captured by a medical imaging apparatus, (Para 29 and Fig. 1 discloses the image diagnosis support device 200 of the present embodiment is provided with a computer (image diagnosis support unit) 20 configured to receive measured data from the medical image acquisition apparatus 100 [medical image of the examination target part] and to perform image diagnosis support processing. Para 30 discloses measured values received by the image diagnosis support device 200 may come from one medical image acquisition apparatus 100, or from a plurality of medical image acquisition apparatuses 100A, 100B, and so on. The medical image acquisition apparatus 100 may be an MRI apparatus, a CT apparatus, and an ultrasonic imaging apparatus, for instance. Para 39 discloses the intermediate index calculator 230 uses the measured values in each group to calculate the intermediate index (S203). For calculating the index, a publicly-known machine learning algorithm or neural network may be employed. In other words, a function with a coefficient decided according to the relation between measured values and an evaluation result (index) having been obtained from another subject that is different from a test subject, or a trained neural network, are used to calculate the intermediate index of the measured values of the group.)
specify a current analysis item related to a predetermined medical disease on the examination target part to perform determination on a state of the examination target part on the basis of the plurality of types of medical information; (Para 36 discloses The measured-value receiving unit 210 captures a plurality of measured values directly from the medical image acquisition apparatus 100, or from the storage unit 40, in response to diagnostic details such as a disease to be determined, which is specified via the UI unit 30 (S201) [a current analysis item related to a predetermined medical disease]. Para 38 discloses a rule for the grouping, on a region-by-region basis or on a measured-value type basis, may be determined in advance. Alternatively, the rule may be determined depending on a target for diagnosis. The rule may be provided by the user via a user interface screen prepared for the image diagnosis support.)
analyze the plurality of types of medical information using a calculator group corresponding to each of the types of medical information, each of calculators included in the calculator group outputting partial analysis information for calculating an analysis result; (Para 30 discloses measured values received by the image diagnosis support device 200 may come from one medical image acquisition apparatus 100, or from a plurality of medical image acquisition apparatuses 100A, 100B, and so on. The medical image acquisition apparatus 100 may be an MRI apparatus, a CT apparatus, and an ultrasonic imaging apparatus, for instance. Paras 36-39 discloses the measured-value receiving unit 210 captures a plurality of measured values directly from the medical image acquisition apparatus 100, or from the storage unit 40, in response to diagnostic details such as a disease to be determined… the group generator 220 divides thus captured multiple measured values into groups (S202). Grouping is performed on the basis of an attribute of the measured value. For example, a plurality of measured values is put into one group on a region-by-region basis, or the measured values in a plurality of regions are put into one group on a measured-value type basis. In this situation, the number of the measured values constituting the group may be the same across the groups, or it may be different group by group. All the measured values may belong to any of the groups, or some of the measured values may not be used for the following index calculation… A rule for the grouping, on a region-by-region basis or on a measured-value type basis, may be determined in advance. Alternatively, the rule may be determined depending on a target for diagnosis. The rule may be provided by the user via a user interface screen prepared for the image diagnosis support. Next, the intermediate index calculator 230 uses the measured values in each group to calculate the intermediate index (S203). For calculating the index, a publicly-known machine learning algorithm or neural network may be employed. In other words, a function with a coefficient decided according to the relation between measured values and an evaluation result (index) having been obtained from another subject that is different from a test subject, or a trained neural network, are used to calculate the intermediate index of the measured values of the group… A machine learning algorithm used for the calculation is selected as appropriate depending on the index to be calculated [where para 40 discloses the comprehensive index calculator 240 merges values of the intermediate index in the respective groups to calculate a comprehensive index (S204), thus disclosing that there are multiple groupings that result in multiple intermediate indexes (See further Fig. 5) and thus multiple calculators for multiple intermediate indexes]. See further: para 73.)
calculate the analysis result with respect to the current analysis item related to the predetermined medical disease on the basis of a combination of the partial analysis information output by each of the calculators a weight of each of the calculators determined according to the current analysis item. (Para 12 discloses a medical image acquisition apparatus of the present invention includes a measurement unit configured to acquire various types of measured values at a plurality of positions in a subject, and a computing unit configured to perform computations using the various types of measured values acquired by the measurement unit, wherein the computing unit includes a group generator configured to divide the various types of measured values into a plurality of groups, an intermediate index calculator configured to calculate an intermediate index from the measured values included in the group on a per-group basis , and a comprehensive index calculator configured to calculate a comprehensive index from values of the intermediate index calculated on a per-group basis. The intermediate index and the comprehensive index are displayed in predetermined forms, for example, on a display unit. Para 40 discloses the comprehensive index calculator 240 merges values of the intermediate index in the respective groups to calculate a comprehensive index (S204). Calculation of the comprehensive index may be weighted-addition of the values of the intermediate index, for example, or it is calculated according to the machine learning algorithm or the neural network, using the relation between the intermediate index and the comprehensive index. As described above, the index may indicate the presence or absence of abnormality, the probability of a certain disease, a degree of disease progression, and so on.)
While Amemiya discloses the above limitations, it does not fully disclose “any two of” the three types of medical information. As presented above, Amemiya discloses, to paraphrase, the medical image and specifically discloses a plurality of medical images from a plurality of medical imaging apparatuses wherein the measured values are received from the plurality of medical imaging apparatuses and then grouped based on a rule and thus discloses a plurality of medical information. However, Amemiya does not fully disclose the additional use of one more medical information from the two remaining options, “biological measurements of the examination target part measured by a medical measurement apparatus including a sensor and a diagnostic result of the examination target part extracted from an electronic medical record.” (Paras 6-8 disclose a disease prediction method according to an embodiment of the present disclosure for achieving the above-described technical problem includes: obtaining a medical image of an object, a photographing time of the medical image, and identification information of the object; acquiring at least one electrocardiogram data corresponding to the imaging timing and the identification information from among the ECG data as ECG data for the object; and corresponding to the imaging timing and the identification information from among the disease information of the plurality of objects acquiring disease information as disease information of the object. Para 17 discloses In this case, the plurality of ECG induction methods may be a method of measuring (or inducing) ECG data for an object using electrodes. The object may refer to a living organism having a heart, such as a human and/or an animal. However, hereinafter, for convenience of description, it is assumed that the object is a person. Paras 39-40 disclose the electrocardiogram measuring apparatus may be implemented as various electronic devices such as a Holter device and/or a wearable device capable of acquiring an electrode waveform from a body…. The electrocardiogram measuring device may be implemented as a body-contact type electronic device…. May be a body contact type electronic device that acquires a user’s electrode waveform… Paras 53-54 disclose the disease prediction device 500 detects abnormalities such as abnormal heart shape or size and calcium deposition in blood vessels through X-ray images of the heart region as well as information on the heart region that triggers the heart rate and beating through the electrocardiogram data can be analyzed effectively… Accordingly, the disease prediction apparatus 500 may improve disease prediction accuracy (or disease diagnosis accuracy) compared to a method of predicting a disease of an object through a medical image or electrocardiogram data of the object.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the image diagnosis support device, program, and medical image acquisition apparatus as taught by Amemiya with the method for predicting disease and apparatus for performing the same as taught by Kwon in order to increase the disease prediction accuracy (or disease diagnosis accuracy) [by utilizing both the medical image and the electrocardiogram] compared to a method of predicting a disease of an object through a medical image or electrocardiogram data of the object [alone] (See Kwon Paras 53-54).
Regarding Claim 13, this claim recites the limitations of Claim 1 and as to those limitations is rejected for the same basis and reasons as disclosed above. The combination of Amemiya and Kwon discloses the following limitation that Amemiya further discloses:
(New) The medical determination support apparatus according to claim 1, wherein each of the calculators is a learning model or a look-up table. (Paras 37-39 disclose a rule for the grouping, on a region-by-region basis or on a measured-value type basis, may be determined in advance. Alternatively, the rule may be determined depending on a target for diagnosis. The rule may be provided by the user via a user interface screen prepared for the image diagnosis support. Next, the intermediate index calculator 230 uses the measured values in each group to calculate the intermediate index (S203). For calculating the index, a publicly-known machine learning algorithm or neural network may be employed. In other words, a function with a coefficient decided according to the relation between measured values and an evaluation result (index) having been obtained from another subject that is different from a test subject, or a trained neural network, are used to calculate the intermediate index of the measured values of the group…A machine learning algorithm used for the calculation is selected as appropriate depending on the index to be calculated [where para 40 discloses the comprehensive index calculator 240 merges values of the intermediate index in the respective groups to calculate a comprehensive index (S204), thus disclosing that there are multiple groupings that result in multiple intermediate indexes (See further Fig. 5) and thus multiple calculators for multiple intermediate indexes]. See further: para 73.)
Regarding Claim 14, this claim recites the limitations of Claim 1 and as to those limitations is rejected for the same basis and reasons as disclosed above. The combination of Amemiya and Kwon discloses the following limitation that Amemiya further discloses:
(New) The medical determination support apparatus according to claim 1, wherein the medical imaging apparatus is any of an ultrasound diagnostic apparatus, an X-ray CT apparatus, a magnetic resonance imaging (MRI) apparatus, or a nuclear medicine examination apparatus. (Para 30 discloses measured values received by the image diagnosis support device 200 may come from one medical image acquisition apparatus 100, or from a plurality of medical image acquisition apparatuses 100A, 100B, and so on. The medical image acquisition apparatus 100 may be an MRI apparatus, a CT apparatus, and an ultrasonic imaging apparatus, for instance)
Regarding Claim 15, this claim recites the limitations of Claim 1 and as to those limitations is rejected for the same basis and reasons as disclosed above. The combination of Amemiya and Kwon discloses the following limitation that Kwon further discloses:
(New) The medical determination support apparatus according to claim 1, wherein the medical measurement apparatus including the sensor is any one of a blood tester, a genetic tester, an electrocardiograph or a cardiac examination apparatus (through the 112b interpretation of claim 15 per the specification). (Paras 6-8 disclose a disease prediction method according to an embodiment of the present disclosure for achieving the above-described technical problem includes: obtaining a medical image of an object, a photographing time of the medical image, and identification information of the object; acquiring at least one electrocardiogram data corresponding to the imaging timing and the identification information from among the ECG data as ECG data for the object; and corresponding to the imaging timing and the identification information from among the disease information of the plurality of objects acquiring disease information as disease information of the object. Para 17 discloses In this case, the plurality of ECG induction methods may be a method of measuring (or inducing) ECG data for an object using electrodes. The object may refer to a living organism having a heart, such as a human and/or an animal. However, hereinafter, for convenience of description, it is assumed that the object is a person. Paras 39-40 disclose the electrocardiogram measuring apparatus may be implemented as various electronic devices such as a Holter device and/or a wearable device capable of acquiring an electrode waveform from a body…. The electrocardiogram measuring device may be implemented as a body-contact type electronic device…. May be a body contact type electronic device that acquires a user’s electrode waveform… Paras 53-54 disclose the disease prediction device 500 detects abnormalities such as abnormal heart shape or size and calcium deposition in blood vessels through X-ray images of the heart region as well as information on the heart region that triggers the heart rate and beating through the electrocardiogram data can be analyzed effectively… Accordingly, the disease prediction apparatus 500 may improve disease prediction accuracy (or disease diagnosis accuracy) compared to a method of predicting a disease of an object through a medical image or electrocardiogram data of the object.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the image diagnosis support device, program, and medical image acquisition apparatus as taught by Amemiya with the method for predicting disease and apparatus for performing the same as taught by Kwon in order to increase the disease prediction accuracy (or disease diagnosis accuracy) [by utilizing both the medical image and the electrocardiogram] compared to a method of predicting a disease of an object through a medical image or electrocardiogram data of the object [alone] (See Kwon Paras 53-54).
Regarding Claim 16, the claim is directed to the method that is implemented by the processor of the apparatus of claim 1 without reciting any further limitations and as such is similarly rejected.
Claim(s) 2-3, 5-6 and 8-11 are rejected under 35 U.S.C. 103 as being unpatentable over Amemiya (US PG Pub 2020/0380676 A1) in view of Kwon (KR 2021/0102102 A) and further in view of Boussios (US PG Pub 2022/0148695 A1).
Regarding Claim 2, this claim recites the limitations of Claim 1 and as to those limitations is rejected for the same basis and reasons as disclosed above. The combination of Amemiya and Kwon discloses the following limitation that Amemiya further discloses:
The medical determination support apparatus according to claim 1, wherein, in [[the]] importance information, [[the]] an importance of each of the types of medical information is associated with a diagnosis situation of the subject, and the processor specifies the importance of each of the calculators included in the calculator group on the basis of the importance information... (Para 33 discloses indexes calculated by the intermediate index calculator 230 and the comprehensive index calculator 240 may include, for example, an index indicating whether a subject is in normal condition or not, an index indicating whether the subject contracts a certain disease or not and the degree of the disease progression, or an index indicating which disease out of multiple diseases (which disease has the highest probability) [diagnosis situation]. Para 38 discloses a rule for the grouping, on a region-by-region basis or on a measured-value type basis, may be determined in advance. Alternatively, the rule may be determined depending on a target for diagnosis. The rule may be provided by the user via a user interface screen prepared for the image diagnosis support.)
While Amemiya discloses the above limitation, the combination of Amemiya and Kwon does not fully disclose the current diagnosis that Boussios discloses:
the analysis unit specifies the importance of each of the calculators included in the calculator group on the basis of the importance information and a current diagnosis situation of the subject. (Para 119 discloses the various weights in the foregoing computations can be determined by a statistical analysis of a patient data set with known outcomes. The statistical analysis can determine which fields of patient data contribute most to a specific outcome in a category. Weights can be assigned to such fields of patient data to compute factor scores and outcome scores for the category. In particular, a weight can be assigned to each diagnosis code and procedure code. This weight can be applied to compute the factor score using that diagnosis code or procedure code.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of the image diagnosis support device, program, and medical image acquisition apparatus as taught by Amemiya and the method for predicting disease and apparatus for performing the same as taught by Kwon with the information system providing explanation of models as taught by Boussios in order to output a more personalized calculation by determining the weights based on the diagnosis code.
Regarding Claim 3, this claim recites the limitations of Claim 1 and as to those limitations is rejected for the same basis and reasons as disclosed above. The combination of Amemiya and Kwon does not fully disclose the following limitation that Boussios discloses:
The medical determination support apparatus according to claim [[1]] 2, wherein the processor calculates the analysis result on the basis of the specified importance of each of the calculators without using some of the calculators in the calculator group. (Para 76 discloses for storing outcome measures, for each category in which a patient is classified, outcome scores over time are stored. Thus, outcome data 730-1 to 730-N includes a category identifier 732, a time 734 and factor scores 736-740 for each factor for which a score is computed. The example shown in FIG. 7 shows five such factor scores. The outcome value 746, computed as a weighted combination of the factor scores, also can be stored. Examples of other data that can be stored is an indication of the method used to compute the outcome score from the factor scores [thus disclosing N possibility of calculators but only calculating scores for those that the patient is categorized under (in the example in Fig. 7: five such factor scores)].)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of the image diagnosis support device, program, and medical image acquisition apparatus as taught by Amemiya and the method for predicting disease and apparatus for performing the same as taught by Kwon with the information system providing explanation of models as taught by Boussios in order to output a more personalized calculation by only utilizing the data that is most relevant to the patient.
Regarding Claim 5, this claim recites the limitations of Claim 4 and as to those limitations is rejected for the same basis and reasons as disclosed above. The combination of Amemiya and Kwon does not fully disclose the following limitation that Boussios discloses:
The medical determination support apparatus according to claim [[4]] 2, wherein the importance of a first calculator for one of the analysis items is different from the importance of a different second calculator, which corresponds to the same type of medical information as the first calculator, for another of the analysis items. (Para 100 discloses the unified condition specific health score, also called the outcome score herein, is calculated from at least one of five factor scores based on an algorithm that separately weights each underlying factor score, and combines the weighted factor scores into a single value. Para 107 discloses for each condition, at each time point, one or more of these condition-specific factors scores are computed, and then weighted and combined to compute an outcome score. Para 108 discloses it also may allow different weights to be provided by panels for the measurements comprising the factor scores as well. For example, a particular group may seek a patient panel to provide input on how to weight the five factor scores for evaluating condition specific outcomes [thus discloses the ability for different weights of each calculator where the calculator is for each factor score] for the one year point. Such a group might also provide input on whether to weight a visual analogue scale or a VR-12 scale [same type of medical information] in the patient reported summary score differently or equally [thus disclosing that the importances can be differently even for the same type of medical information]. The value of this flexibility is that different end users may find that different weightings provide more information to their particular stakeholder group or for particular decision making. Para 119 discloses the various weights in the foregoing computations can be determined by a statistical analysis of a patient data set with known outcomes. The statistical analysis can determine which fields of patient data contribute most to a specific outcome in a category. Weights can be assigned to such fields of patient data to compute factor scores and outcome scores for the category. In particular, a weight can be assigned to each diagnosis code and procedure code. This weight can be applied to compute the factor score using that diagnosis code or procedure code [analysis items based on Applicant’s specification para 49).) )
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of the image diagnosis support device, program, and medical image acquisition apparatus as taught by Amemiya and the method for predicting disease and apparatus for performing the same as taught by Kwon with the information system providing explanation of models as taught by Boussios in order to determine that different weighting provide more information to a particular stakeholder group or for particular decision making (Boussios Para 108).
Regarding Claim 6, this claim recites the limitations of Claim 4 and as to those limitations is rejected for the same basis and reasons as disclosed above. The combination of Amemiya and Kwon discloses the following limitation that Amemiya further discloses:
The medical determination support apparatus according to claim [[4]] 2, wherein the processor is further configured to: determine a state of the examination target part on the basis of an output of a comprehensive determination learning model, which has been trained to predict the state of the examination target part on the basis of the plurality of analysis results for the plurality of analysis items and to output the state, in a case where the plurality of analysis results (Para 12 discloses a medical image acquisition apparatus of the present invention includes a measurement unit configured to acquire various types of measured values at a plurality of positions in a subject, and a computing unit configured to perform computations using the various types of measured values acquired by the measurement unit, wherein the computing unit includes a group generator configured to divide the various types of measured values into a plurality of groups, an intermediate index calculator configured to calculate an intermediate index from the measured values included in the group on a per-group basis, and a comprehensive index calculator configured to calculate a comprehensive index from values of the intermediate index calculated on a per-group basis [a state on the basis of a plurality of analysis results]. The intermediate index and the comprehensive index are displayed in predetermined forms, for example, on a display unit. Para 40 discloses the comprehensive index calculator 240 merges values of the intermediate index in the respective groups to calculate a comprehensive index (S204). Calculation of the comprehensive index may be weighted-addition of the values of the intermediate index, for example, or it is calculated according to the machine learning algorithm or the neural network, using the relation between the intermediate index and the comprehensive index. As described above, the index may indicate the presence or absence of abnormality, the probability of a certain disease, a degree of disease progression, and so on [thus the comprehensive index is a state]. Paras 73-76 discloses the index pm thus obtained represents the probability of a certain disease (e.g., neurodegenerative disease, cerebral infarction, and so on) estimated from the measured value xm of the m-th group. Transformation performed as to each of the groups generated by the group generator 220 allows calculation of one intermediate index (in the present example, the probability pm of disease) from each group [analysis results based on analysis items]… For example, the comprehensive index uses as the input, a vector given by aligned numerical values of the intermediate index calculated by the intermediate index calculator, so as to calculate the probability of a certain disease, as the comprehensive index according to Equation 3).)
Regarding Claim 8, this claim recites the limitations of Claim 6 and as to those limitations is rejected for the same basis and reasons as disclosed above. The combination of Amemiya and Kwon discloses the following limitation that Amemiya further discloses:
The medical determination support apparatus according to claim 6, wherein the processor is further configured to: display the medical information, the determined state on a display unit. (Abstract discloses the intermediate index and the comprehensive index are displayed on a display unit in a display mode such as numerical values and in the form of an image. Para 7 discloses a method for calculating a feature of a region of interest (ROI) in an image, and displaying an index for diagnosis, such as the degree of malignancy, with the use of neural network. Para 34 discloses the UI unit 30 displays the measured values received by the measured-value receiving unit 210 [the medical information wherein the measured values are determines from the medical images] and the indexes calculated by the computer 20 (the intermediate index and the comprehensive index) [the determined state]. In addition, the UI unit 30 receives entries of conditions to perform imaging, and an instruction from the user for creating an image and calculating the indexes.)
Regarding Claim 9, this claim recites the limitations of Claim 8 and as to those limitations is rejected for the same basis and reasons as disclosed above. The combination of Amemiya and Kwon discloses the following limitation that Amemiya further discloses:
The medical determination support apparatus according to claim 8, wherein the display control unit displays a screen for selecting either the plurality of pieces of medical information,the determined state on the display unit. (Abstract discloses the intermediate index and the comprehensive index are displayed on a display unit in a display mode such as numerical values and in the form of an image. Para 7 discloses a method for calculating a feature of a region of interest (ROI) in an image, and displaying an index for diagnosis, such as the degree of malignancy, with the use of neural network. Para 34 discloses the UI unit 30 displays the measured values received by the measured-value receiving unit 210 and the indexes calculated by the computer 20 (the intermediate index and the comprehensive index). In addition, the UI unit 30 receives entries of conditions to perform imaging, and an instruction from the user for creating an image and calculating the indexes. Para 36 discloses the measured-value receiving unit 210 captures a plurality of measured values directly from the medical image acquisition apparatus 100, or from the storage unit 40, in response to diagnostic details such as a disease to be determined, which is specified via the UI unit 30 (S201) [thus displays a screen for selecting... the determined state on the display unit]. Para 65 discloses for the image diagnosis support, the measured-value receiving unit 210 receives from a user via the input unit 116, designation of information related to required diagnosis, and reads necessary measured values from those stored in the storage unit 112 (FIG. 1: storage unit 40) (S201). Para 69 discloses specifically, a specific-data entry area 511 displayed on the measured-value receiving area 510 receives user's operation such as entry of the subject name and measured values being specified. Then, in response to thus received entries, measured values stored in the storage unit 112 are read out, thereby receiving the measured values. Thus received measured values may be displayed in a display area 512 for the entered measured values, facilitating the user to ascertain the measured values. See further: Para 29.)
Regarding Claim 10, this claim recites the limitations of Claim 8 and as to those limitations is rejected for the same basis and reasons as disclosed above. The combination of Amemiya and Kwon does not fully disclose the following limitation that Boussios discloses:
The medical determination support apparatus according to claim 8, wherein processor displays so that the difference between the importance is distinguishable (Para 69 discloses a client computer 154 can present a graphical user interface that presents, for each patient, the outcome score for a selected condition for the patient, whether at a current point in time, a past point in time or over a period of time. The graphical user interface can present information about how the outcome score is computed, based on the weighting function and the underlying scores for the different factors. [thus “discriminating the importance of the medical information”].)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of the image diagnosis support device, program, and medical image acquisition apparatus as taught by Amemiya and the method for predicting disease and apparatus for performing the same as taught by Kwon with the information system providing explanation of models as taught by Boussios in order to identify how the outcome score is computed and show a user how the different weightings provide more information to a particular stakeholder group or for particular decision making (Boussios Para 108).
Regarding Claim 11, the claim is directed to the computer readable storage medium implementing the method as performed by the processor of the apparatus of claim 1 and further recites a non-transitory computer-readable storage medium storing a medical determination support program causing a computer to function (See Amemiya Para 31, disclosing a computer 20 that includes a CPU and a memory… Para 32 discloses the CPU reads programs stored in advance in the memory and executes those programs, thereby allowing software to implement functions of those units as described above. See Boussios Para 181 an example computer 600 includes at least one processing unit 602 and memory 604… The memory 604 may include.. non-volatile devices (such as a read-only memory, flash memory, and the like)… and optionally including any memory available in a processing device. Other memory such as dedicated memory or registers also can reside in a processing unit) and is similarly rejected.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of the image diagnosis support device, program, and medical image acquisition apparatus as taught by Amemiya and the method for predicting disease and apparatus for performing the same as taught by Kwon with the non-volatile devices (such as a read-only memory, flash memory, and the like) as taught by Boussios in order to retain stored data even when disconnected from a power source.
Regarding Claim 12, this claim recites the limitations of Claim 1 and as to those limitations is rejected for the same basis and reasons as disclosed above. The combination of Amemiya and Kwon does not fully disclose the following limitation that Boussios discloses:
(New) The medical determination support apparatus according to claim 1, wherein the processor calculates the analysis result with respect to the current analysis item without using some of the calculators. (Para 76 discloses for storing outcome measures, for each category in which a patient is classified, outcome scores over time are stored. Thus, outcome data 730-1 to 730-N includes a category identifier 732, a time 734 and factor scores 736-740 for each factor for which a score is computed. The example shown in FIG. 7 shows five such factor scores. The outcome value 746, computed as a weighted combination of the factor scores, also can be stored. Examples of other data that can be stored is an indication of the method used to compute the outcome score from the factor scores [thus disclosing N possibility of calculators but only calculating scores for those that the patient is categorized under (in the example in Fig. 7: five such factor scores)].)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of the image diagnosis support device, program, and medical image acquisition apparatus as taught by Amemiya and the method for predicting disease and apparatus for performing the same as taught by Kwon with the information system providing explanation of models as taught by Boussios in order to output a more personalized calculation by only utilizing the data that is most relevant to the patient.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Amemiya (US PG Pub 2020/0380676 A1) in view of Kwon (KR 2021/0102102 A), further in view of Boussios (US PG Pub 2022/0148695 A1), and Krishnan (US PG Pub 2005/0020903 A1).
Regarding Claim 7, this claim recites the limitations of Claim 6 and as to those limitations is rejected for the same basis and reasons as disclosed above. While Amemiya Para 69 discloses, “Next, the measured-value receiving unit 210 receives given various types of measured values at given multiple positions within a living body,” the combination of Amemiya, Kwon, and Boussios does not fully disclose the following limitation that Krishnan discloses:
The medical determination support apparatus according to claim 6, wherein the examination target part is a heart, the processor outputs a disease state related to each of a plurality of disease types related to the heart as the plurality of analysis results, and the processor comprehensively determines a state of the heart of the subject on the basis of the disease state related to each of the plurality of disease types. (Para 11 discloses include CAD (computer-aided diagnosis) systems and applications for cardiac imaging, which implement automated methods for extracting and analyzing relevant features/parameters from a collection of patient information (including image data and/or non-image data) of a subject patient to provide automated assistance to a physician for various aspects of physician workflow including, for example, automated assessment of regional myocardial function through wall motion analysis, automated diagnosis of heart diseases and conditions such as cardiomyopathy, coronary artery disease and other heart-related medical conditions, and other automated decision support functions to assist physician workflow. Para 37 discloses for screening, the CAD system (10) can generate and output decisions as discussed above, including likelihood of disease. Para 39 discloses the classification module (24) comprises a classification method (24-1) (or classification engine) that analyzes the combined extracted parameters using one or more classification models, which are trained/dynamically adapted via model builder (24-2), to generate information that is used to provide diagnostic and decision support. The diagnostic/workflow assistance module (25) includes one or more methods for implementing functions such as described above with reference to FIG. 1 (e.g., providing a regional assessment of myocardial function, providing a set of cases similar to a current case, providing a score showing the likely benefit of additional features that would improving a confidence of a regional assessment, etc.). Para 45 discloses the classification results will be presented to the user as a wall motion "score" for various segments of the left ventricle of the heart in accordance with a recommended standard of the American Society of Echocardiography (ASE). In particular, under the ASE standard, the Left Ventricle is divided into a plurality of segments (e.g., 16 or 17). The ASE recommends using standard ultrasound views (A4C, A2C, PSAX, PLAX, ALAX views in B-mode) to obtain image data for the various segments and analyzing such image data to assign each segment a wall motion score as follows: 1=normal; 2=hypokinesis; 3=akinesis; 4=dyskinesis; and 5=aneurysmal [various disease states for various disease types]. See further: Para 2)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of the image diagnosis support device, program, and medical image acquisition apparatus as taught by Amemiya, the method for predicting disease and apparatus for performing the same as taught by Kwon, and the information system providing explanation of models as taught by Boussios with the systems and methods for automated diagnosis and decision support for heart related diseases and conditions as taught by Krishnan in order to detect heart related diseases as early as possible in order to implement appropriate, effective, and cost-effective treatment to reduce fatality (Krishnan Para 3).
Response to Arguments
Applicant’s remarks filed 1/30/2026 with respect to 35 U.S.C. § 112(b) have been fully considered, and are persuasive in light of the amendments made to claims 5 and 10 and the removal of the indefinite portion from claim 11. As such, the previous 112(b) rejections have been withdrawn.
Applicant’s arguments filed 1/30/2026 with respect to 35 U.S.C. § 101 have been fully considered, but are not persuasive.
The Applicant argues that the operations rely on specialized medical devices and machine-executed processing, and therefore should not be interpreted as capable of being performed by human minds nor categorized as human activities. The Examiner respectfully disagrees.
First, the Examiner submits that the abstract idea was not characterized as being directed to a mental process. The claimed invention was characterized as falling under Certain Methods of Organizing Human activity.
Second, merely implementing an abstract idea with machine-executed processing (such as via a processor or non-transitory computer-readable storage medium storing a medical determination support program causing a computer [to perform a method] as the claims of the instant application recite) is recited at a high-level of generality such that it amounts to no more than mere instructions to implement an abstract idea by adding the words ‘apply it’ (or an equivalent) with the judicial exception.
Third, MPEP 2106. 04(a)(2)(II) states that a claimed invention is directed to certain methods of organizing human activity if the identified claim elements contain limitations that encompass fundamental economic principles or practices, commercial or legal interactions, or managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). The Examiner submits that the identified claim elements represent a series of rules or instructions that a person or persons, with or without the aid of a computer, would follow to calculate an analysis result based on a weighted combination of partial analysis. The specification broadly discloses in paragraph 51 that “each calculator may be any type of calculator as long as it can output the partial analysis information on the corresponding analysis item on the basis of the corresponding type of medical information” and paragraph 2 discloses “a doctor determines (for example, diagnoses) a determination target part of a subject on the basis of a plurality of types of medical information on the subject acquired by one or a plurality of medical apparatuses” and thus discloses that determining of a determination target part on the basis of a plurality of types of medical information is a human task. Applicant has not pointed to anything in the claims that fall outside of this characterization that was not already analyzed as an additional element (and not as a part of the abstract idea). Because the claim elements fall under a series of rules or instructions that a person or persons would follow to calculate an analysis result based on a weighted combination of partial analysis, the claimed invention is directed to an abstract idea.
Further, the Applicant argues that the claimed invention “improves diagnostic accuracy by dynamically weighting the partial analysis information generated by the calculation group… therefore provides a technological improvement in medical determination support systems.” The Examiner respectfully disagrees. MPEP 2106.04(d)(1) and MPEP 2106.05(a) indicates that a practical application may be present where the claimed invention provides a technical solution to a technical problem. See, e.g., DDR Holdings, LLC. v. Hotels.com, L.P., 773 F.3d 1245, 1259 (Fed. Cir. 2014) (finding that claiming a website that retained the “look and feel” of a host webpage provided a technological solution to the problem of retention of website visitors by utilizing a website descriptor that emulated the “look and feel” of the host webpage, where the problem arose out of the internet and was thus a technical problem). The need for improving diagnostic accuracy is not a problem caused by the computer that is involved in the process. At best, Applicant’s identified problem is a business problem. Because no technological problem is present, the claims do not provide a practical application.
Further, MPEP 2106.04(d)(1) states "the word 'improvements' in the context of this consideration is limited to improvements to the functioning of a computer or any other technology/technical field, whether in Step 2A Prong Two or in Step 2B." Here, there is no improvement to the computer nor is there an improvement to another technology. The medical determination support apparatus is implemented on a processor. The processor is not improved in any way, it is performing the analysis as expected and is recited at a high-level of generality such that it amounts to no more than mere instructions to implement an abstract idea by adding the words ‘apply it’ (or an equivalent) with the judicial exception. Further, the claim specifically discloses, “calculating the analysis result with respect to the current analysis item related to the predetermined medical disease on the basis of… a weight of each of the calculators determined according to the current analysis item,” which is a part of the abstract idea as presented above. The claim does not disclose how the weight of each of the calculators is determined and therefore, no computer or other technology is recited as being involved in determining the weight for the calculators. Because neither an improvement to the functioning of a computer or any other technology/technical field is present in the claims and the specific limitation argued by the Applicant is a part of the abstract idea, an improvement to technology is not present and there is no practical application.
Applicant’s arguments filed 1/30/2026 with respect to 35 U.S.C. § 102 have been fully
considered and are persuasive regarding the newly added limitations. Therefore, the previous 35 U.S.C.
§ 102 and 103 rejections have been withdrawn. However, upon further consideration, a new grounds of rejection under 35 U.S.C. § 103 necessitated by Applicant’s amendments are as disclosed above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SARA J MORICE DE VARGAS whose telephone number is (703)756-4608. The examiner can normally be reached M-F 8:30-5:30 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, Peter H. Choi can be reached at (469)295-9171. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/SARA JESSICA MORICE DE VARGAS/Examiner, Art Unit 3681
/PETER H CHOI/Supervisory Patent Examiner, Art Unit 3681
Prosecution Insights