DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “determine, based on an output from a first machine learning model that has learned a relationship between health examination data from a first subject and a result of brain examination of the first subject when health examination data from a second subject, a result of brain examination of the second subject is input to the first machine learning model, a result of brain examination of the second subject; and determine, based on an output from a second machine learning model that has learned a relationship between a result of brain examination of a third subject and a result of disease diagnosis of the third subject when at least the result of brain examination of the second subject is input to the second machine learning model, a result of disease diagnosis of the second subject; and wherein the health examination data includes blood examination data, and wherein the result of brain examination includes at least one of results of a questionnaire test on cognitive function and a brain atrophy index indicating the degree of brain atrophy.”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “a disease diagnosis result determination device,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “a disease diagnosis result determination device,” language, “determine” in the context of this claim encompasses the user manually making determinations.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. This judicial exception is not integrated into a practical application. In particular, the claim only recites one additional element – using a device to perform determining. The device in both steps is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of applying rules to data) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
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 element of using a device to perform both the steps 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. The claim is not patent eligible.
The dependent only further limit the abstract idea as in the independent claim, as they further limit the same abstract idea as the independent claims and do not therefore, in combination, recite significantly more than the abstract idea or provide a practical application of the abstract idea.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-10 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by U.S. Patent Application Publication 2019/0110754 to Rao et al.
As to claim 1, 6, and 7, discloses a disease diagnosis result determination device the disease diagnosis result determination device comprising an integrated circuit configured to:
determine, based on an output from a first machine learning model that has learned a relationship between health examination data from a first subject and a result of brain examination of the first subject when health examination data from a second subject, a result of brain examination of the second subject is input to the first machine learning model, a result of brain examination of the second subject (Rao [0073]-[0075], [0034], and [0093]); and
determine, based on an output from a second machine learning model that has learned a relationship between a result of brain examination of a third subject and a result of disease diagnosis of the third subject when at least the result of brain examination of the second subject is input to the second machine learning model, a result of disease diagnosis of the second subject; and (Rao [0073]-[0075], [0034], and [0093]).
wherein the health examination data includes blood examination data (Rao [0141] see laboratory data), and
wherein the result of brain examination includes at least one of include a questionnaire test on cognitive function (Rao [0128], [0141] wherein the results of the questions are used to assess neurological disorders therefore are a questionnaire test on cognitive function).
As to claim 2, see the discussion of claim 2, additionally, discloses disease diagnosis result determination device wherein the result of brain examination includes results of a plurality of types of brain examinations (Rao [0087]-[0093]),
the first machine learning model has learned relationships corresponding to a plurality of types of learning results for the respective types of brain examinations (Rao [0087]-[0093]), and
the integrated circuit is configured to determine, based on outputs from the first machine learning model corresponding to the learned relationships for the respective types of brain examinations and based on the health examination data from the second subject, each of the results of the plurality of types of brain examinations of the second subject (Rao [0087]-[0093]).
As to claim 3, see the discussion of claim 2, additionally, discloses the disease diagnosis result determination device wherein the integrated circuit is configured to;
acquire a result of brain examination obtained by performing one or some of the types of brain examinations of the second subject in advance (Rao [0087]-[0093]), and
use the result of brain examination acquired by the brain examination and make the determination for the one or some of the types of brain examinations, instead of the result of brain examination of the second subject determined by the integrated circuit based on the output from the first machine learning model (Rao [0087]-[0093]).
As to claim 4, see the discussion of claim 1, additionally, discloses the disease diagnosis result determination device wherein
the integrated circuit is configured to determine a result of brain examination of the second subject based on an output from the first machine learning model and the health examination data from the second subject by using statistics of health examination data from a plurality of fourth subjects as part of the health examination data from the second subject (Rao [0087]-[0093]).
As to claim 5, see the discussion of claim 1, additionally, discloses the disease diagnosis result determination device
Wherein the integrated circuit is configured to output, after the disease diagnosis result determination unit determines the result of disease diagnosis, a set of the results of brain examination of the second subject used to determine the result of disease diagnosis and the result of disease diagnosis (Rao [0155]).
As to claim 8, see the discussion of claim 1, additionally Rao discloses wherein each of the first machine learning model and the second machine learning model is a multilayer neural network (Rao [0052], [0060]-[0061 see convolutional neural network).
As to claim 9, see the discussion of claim 8, additionally, Rao discloses wherein the first machine learning model and the second machine learning model are connected to each other such that the output from an output layer of the first machine learning model is input into an input layer of the second machine learning model (Rao [0052], [0060]-[0061], [0101]-[0104] see convolutional neural network and trained from subjects classified as possessing a certain neurological disorder).
As to claim 10, see the discussion of claim 8, additionally, Rao discloses wherein parameters of the first machine learning model are determined by learning the relationship between health examination data from a first subject and a result of brain examination of the first subject, wherein parameters of the second machine learning model are determined by learning the relationship between a result of brain examination of a third subject and a result of disease diagnosis of the third subject (Rao [0052], [0060]-[0061], [0101]-[0104] see convolutional neural network and trained from subjects classified as possessing a certain neurological disorder).
Response to Arguments
Applicant's arguments filed 6/2/2025 have been fully considered but they are not persuasive. With respect to the 101 rejection, Applicant argues that processing specific and complex data is too complicated to be performed by a human mind. The claim merely requires data of three people to be considered in the machine learning (mathematical) algorithm. A human could perform these calculations mentally or with pen and paper. Additionally, applicant argues that the basic blood examination data enables cognitive function changes and structural changes in the brain to be predicted. This feature is not claimed. Applicant additionally argues that this invention can be used as a screening test for dementia and provides a practical application of the abstract idea. This feature is not claimed.
The previous rejections under 112 are withdrawn in light of Applicants amendments.
Applicant argues with respect to the 102 rejection that Rao does not teach a learned relationship between health examination data from a first and second subject. Rao discloses in [0093] “An annotated dataset covering a range of healthy and diseased patients will be assembled and used to train and validate the machine learning system”. Applicant argues that Rao does not teach a result of brain examination. There is no special definition of this term and Examiner relies upon the broadest reasonable interpretation of the claim which would encompass a result of any brain related examination (imaging and clinical). A clinical determination of diagnosis as in Rao is a result of brain examination. Applicant argues that Rao does not teach examination data including blood examination data. Rao discloses considering laboratory data in [0141] as well as answers to set of questions (which fall under the broadest reasonable interpretation of questionnaire tests on cognitive function).
The 102 rejection is therefore maintained.
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.
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/ELIZA A LAM/Primary Examiner, Art Unit 3681