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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed 8-12-2026 has been entered.
Status of Claims
This action is a non-final rejection
Claims 1-11, 15, 17-18 are pending
Claims 12-14, 16 were cancelled
Claims 1-11, 15, 17 were amended
Claims 1-11, 15, 17-18 are rejected under 35 USC § 101
Priority
Acknowledgement is made of Applicant’s claim for a foreign priority date of 5-4-2023
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 7-8-2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 1-11, 15, 17-18 are not patent eligible because the claimed invention is directed to an abstract idea without significantly more.
Analysis
First, claims are directed to one or more of the following statutory categories: a process, a machine, a manufacture, and a composition of matter. Regarding claims 1-11, 15, 17-18 they recite an abstract idea of diagnosing and treating mild cognitive impairment, dementias and neurodegenerative diseases.
Independent Claim 1 is rejected under 35 U.S.C 101 based on the following analysis.
-Step 1 (Does the claim fall within a statutory category? YES): claim 1 recites a method for diagnostics of mild cognitive impairment, dementias and neurodegenerative diseases.
-Step 2A Prong One (Does the claim fall within at least one of the groupings of abstract ideas?: YES):
A method .. for diagnostics and finding treatments for mild cognitive impairment, dementias and neurodegenerative diseases, comprising:
B. collecting brain imaging data, laboratory data, and functional data from a group of cognitively normal individuals;
C. collecting brain imaging data, laboratory data, and functional data from patients with confirmed cases of at least one diagnosis from a plurality of diseases;
D. collecting brain imaging data, laboratory data, and functional data from an examinee with unknown diagnosis;
E. entering at least two types of diagnostic data from steps B and C;
F. preprocessing acquired brain images to generate brain-imaging features or radiomics data, comprising at least one of:
image registration to a template space, correction of intensity nonuniformity, background removal, skull stripping, voxel-intensity scaling, averaging voxel values along anatomical axes, down-sampling, or calculating voxel-based or surface-based morphometry data;
G. training, .. a plurality of disease-specific .. regression models, wherein each disease-specific .. regression model is trained on diagnostic data of either cognitively normal individuals or patients with a confirmed diagnosis, and wherein each model predicts diagnostic data of one type from diagnostic data of at least one other type;
H. producing, .. a classification .. that identifies at least one disease-specific .. regression model that optimally fits an individual case by analyzing prediction errors of the disease-specific .. regression models, and calculates probabilities for the diseases from the plurality of diseases;
I. assembling an ..model from the disease-specific .. regression models and the classification .., and deploying the .. model ..;
J. entering the diagnostic data of the examinee into .. the ..model deployed thereon, wherein the .. model predicts one type of data from at least one other type, and the classification ..uses deviations from the disease- .. regression models to find the best-fitting model, calculate probabilities for different diagnoses, and output at least one diagnosis with the highest probability; and
K. selecting, .., at least one treatment option from the list of treatment options stored therein that is feasible for the output diagnosis, thereby providing an indication for a cognition-focused intervention;
belongs to certain methods of organizing human activity under managing personal behavior or relationships or interactions between people as it recites the abstract idea of “diagnosing and treating mild cognitive impairment, dementias and neurodegenerative diseases”. (refer to MPP 2106.04(a)(2)). Accordingly this claim recites an abstract idea.
-Step 2A Prong Two (Are there additional elements in the claim that imposes a meaningful limit on the abstract idea? NO). Claim 1 recites:
operating a computing system;
providing a machine-learning system and a computing device, wherein the computing device comprises a memory for storing reference subject datasets and a list of treatment options for each diagnosis, and a processing unit for running an ensemble model;
machine- learning system;
cross-modal regression models;
ensemble model;
classification module;
Amounting to mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea. (refer to MPEP 2106.05(f)). Accordingly, these additional elements, when considered separately and as an ordered combination do not integrate the judicial exception/abstract idea into a “practical application” of the judicial exception because they do not impose any meaningful limit on practicing the judicial exception.
-Step 2B (Does the additional elements of the claim provide an inventive concept?: NO. As discussed previously with respect to Step 2A Prong Two, claim 1 recites:
operating a computing system;
providing a machine-learning system and a computing device, wherein the computing device comprises a memory for storing reference subject datasets and a list of treatment options for each diagnosis, and a processing unit for running an ensemble model;
machine- learning system;
cross-modal regression models;
ensemble model;
classification module.
Amounting to mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea. (refer to MPEP 2106.05(f)) Accordingly, even when viewed as a whole the claim does not provide an inventive concept (significantly more than the abstract idea) and hence the claim is ineligible.
Dependent Claims:
Step 2A Prong One: The following dependent claims recite additional limitations that further define the abstract idea of “diagnosing and treating mild cognitive impairment, dementias and neurodegenerative diseases”: claims 2-11, 15, 17-18.
Step 2A Prong Two: (Are there additional elements in the claim that imposes a meaningful limit on the abstract idea? NO). The following dependent claims 2-3, 6, 8-11, 15, 17-18 amount to no more than mere instructions to apply the exception using a generic computer, or merely using a computer as a tool to implement the abstract idea as even in combination, these additional elements do not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea itself. (refer to MPEP 2106.05(f)). Accordingly, the claims as a whole do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Step B: (Does the additional elements of the claim provide an inventive concept?: NO). As discussed previously with respect to Step 2A Prong Two, the following dependent claims 2-3, 6, 8-11, 15, 17-18 amount to mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea. (refer to MPEP 2106.05(f)). Accordingly, the additional elements alone, and in combination do not provide an inventive concept (significantly more than the abstract idea) and hence the claim is ineligible.
Prior Art Made of Record
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure, and is listed in the attached form PTO-892 (Notice of References Cited). Unless expressly noted otherwise by the Examiner, all documents listed on form PTO-892 are cited in their entirety.
Collins et al (US 2008/0101665 A1)- SYSTEMS AND METHODS OF CLINICAL STATE PREDICTION UTILIZING MEDICAL IMAGE DATA – teaches: a method for predicting a clinical state of a subject based on image data obtained from a Volume Of Interest in the subject. The method comprise the establishment of a predictive model that relates image features and the future evolution of a clinical state.
Tsokos (US 2023/0225668)- SYSTEMS, METHODS, AND MEDIA FOR PREDICTING A CONVERSION TIME OF MILD COGNITIVE IMPAIRMENT TO ALZHEIMER'S DISEASE IN PATIENTS– teaches: systems, methods, and media for predicting the conversion time of Mild Cognitive Impairment (MCI) to Alzheimer’s Disease (AD) in a patient are provided. In some embodiments, a system include a memory and a processor coupled to the memory. The processor is configured to: receive a plurality of risk factor indications and a plurality of interaction indications of a patient. Each interaction indication is an indication of interaction between two risk factor indications of the plurality of risk factor indications. The processor is further configured to obtain a trained machine learning model; apply the plurality of risk factor indications and the plurality of interaction indications to the trained machine learning model; and output a result based on the trained machine learning model
Ito (US 20250191768 A1) - COMBINATION OF BIOMARKERS, AND METHOD FOR DETECTING COGNITIVE DYSFUNCTION OR RISK THEREOF BY USING SAID COMBINATION - teaches: provides a cognitive impairment determination system comprising an information processing device that executes a determination step of determining presence or absence cognitive impairment or risk of cognitive impairment, based on amounts of the following biomarkers (a), (b), (c), (d), and (e) contained in a biological sample: (a) a biomarker consisting of an intact protein of Apolipoprotein A1 comprising an amino acid sequence represented by SEQ ID NO: 1, or a partial peptide thereof, (b) a biomarker consisting of an intact protein of Transthyretin comprising an amino acid sequence represented by SEQ ID NO: 2, or a partial peptide thereof, (c) a biomarker consisting of an intact protein of Complement C3 having an amino acid sequence represented by SEQ ID NO: 3, or a partial peptide thereof, (d) a biomarker Aβ1-40 consisting of a peptide having an amino acid sequence represented by SEQ ID NO: 4, and (e) a biomarker Aβ1-42 consisting of a peptide having an amino acid sequence represented by SEQ ID NO: 5.
Response to Arguments
Applicant's arguments filed 8-12-2026, have been fully considered but not found
persuasive.
Applicant amended independent claim 1, in addition to dependent claims 1-11, 15, 17, cancelling claims 12-14, 16, and adding claim 18, as posted in the above analysis with additions underlined and deletions as .
In response to applicant's arguments regarding claim rejection under 35 U.S.C § 101.
Several steps are taken in the analysis as to whether an invention is rejected under 101. The first step is to determine if the claim falls within a statutory category. In this case it does for claim 1 since the claims recites a method for diagnostics of mild cognitive impairment, dementias and neurodegenerative diseases.
The second step under 2A prong one is to determine if the claims recite an abstract idea, which would be the case if the invention can be grouped as either: a) mathematical concepts; (b) mental processes; or (c) certain methods of organizing human activity (encompassing (i) fundamental economic principles, (ii) commercial or legal interactions or (iii) managing personal behavior or relationships or interactions between people). The current invention is classified as an abstract idea since it may be grouped under certain methods of organizing human activity under managing personal behavior or relationships or interrelations between people as it recites “diagnosing and treating mild cognitive impairment, dementias and neurodegenerative diseases”.
The third step under 2A Prong Two is to determine if additional elements in the claim imposes a meaningful limit on the abstract idea in order to integrate it into a practical idea. The current invention does not represent a practical idea since the additional elements amount to mere instructions to implement an abstract idea on a computer, or merely use a generic computer as a tool to implement the abstract idea.
the fourth step under 2B is to determine if additional elements of the claim provide an inventive concept. An invention may be classified as an inventive concept if a computer-implemented processes is determined to be significantly more than an abstract idea (and thus eligible), where generic computer components are able in combination to perform functions that are not merely generic, and non-conventional even if generic computer operations on a generic computing device is used to implement the abstract idea.
Step 2A Prong ONE
The Applicant argues that independent claim 1 is directed to a method of operating a computing system for diagnostics and finding treatments for mild cognitive impairment, dementias and neurodegenerative diseases, not merely to diagnosing disease in the abstract. The amended claim recites a concrete technical system comprising a machine-learning system and a computing device with a memory and processing unit that cooperate to: preprocess brain images, train disease-specific cross-modal regression models, produce a classification module, assemble and run an ensemble model, output a diagnosis with the highest probability, and select a feasible treatment option. As a result the Applicant submits that claim 1 is directed to a non-abstract, technology-rooted category.
The Examiner disagrees since the Applicant’s argument is not persuasive. The method to select the abstract idea is to strip the additional elements from the claims. The Arguments presented by the Applicant is one where additional elements are interspersed with the abstract idea, and for the sake of the analysis they need to be separated out as explained below.
As seen below the recited boldened words constitute the abstract idea after stripping the un-boldened additional elements of amended limitation of claim 1:
A method of operating a computing system for diagnostics and finding treatments for mild cognitive impairment, dementias and neurodegenerative diseases, comprising:
A. providing a machine-learning system and a computing device, wherein the computing device comprises a memory for storing reference subject datasets and a list of treatment options for each diagnosis, and a processing unit for running an ensemble model;
B. collecting brain imaging data, laboratory data, and functional data from a group of cognitively normal individuals;
C. collecting brain imaging data, laboratory data, and functional data from patients with confirmed cases of at least one diagnosis from a plurality of diseases;
D. collecting brain imaging data, laboratory data, and functional data from an examinee with unknown diagnosis;
E. entering at least two types of diagnostic data from steps B and C into the machine- learning system;
F. preprocessing acquired brain images to generate brain-imaging features or radiomics data, comprising at least one of:
image registration to a template space, correction of intensity nonuniformity, background removal, skull stripping, voxel-intensity scaling, averaging voxel values along anatomical axes, down-sampling, or calculating voxel-based or surface-based morphometry data;
G. training, by the machine-learning system, a plurality of disease-specific cross-modal regression models, wherein each disease-specific cross-modal regression model is trained on diagnostic data of either cognitively normal individuals or patients with a confirmed diagnosis, and wherein each model predicts diagnostic data of one type from diagnostic data of at least one other type;
H. producing, by the machine-learning system, a classification module that identifies at least one disease-specific cross-modal regression model that optimally fits an individual case by analyzing prediction errors of the disease-specific cross-modal regression models, and calculates probabilities for the diseases from the plurality of diseases;
I. assembling an ensemble model from the disease-specific cross-modal regression models and the classification module, and deploying the ensemble model at the computing device;
J. entering the diagnostic data of the examinee into the computing device with the ensemble model deployed thereon, wherein the ensemble model predicts one type of data from at least one other type, and the classification module uses deviations from the disease- specific cross-modal regression models to find the best-fitting model, calculate probabilities for different diagnoses, and output at least one diagnosis with the highest probability; and
K. selecting, by the computing device, at least one treatment option from the list of treatment options stored therein that is feasible for the output diagnosis, thereby providing an indication for a cognition-focused intervention
The selected abstract idea (boldened limitations) of claim 1 belong to certain methods of organizing human activity under managing personal behavior or relationships or interrelations between people as it recites “diagnosing and treating mild cognitive impairment, dementias and neurodegenerative diseases”. (refer to MPP 2106.04(a)(2)). Accordingly independent claim 1 recites an abstract idea.
Step 2A Prong TWO
The Applicant argues that even if the amended claims 1 recites an abstract idea, they recite additional elements that integrate the judicial exception into a practical application. The Applicant submits that claim 1, as a whole, is more than just including additional elements that are merely generic computer implementation. Amended claim 1 is not generically directed to "apply diagnosis on a computer", it recites a computing system comprising a machine-learning system and a computing device that perform: (a) preprocessing acquired brain images to generate brain-imaging features or radiomics data using defined algorithms (image registration, intensity correction, background removal, skull stripping, voxel- intensity scaling, averaging along anatomical axes, down-sampling, or calculating morphometry data); (b) training a plurality of disease-specific cross-modal regression models, each trained on diagnostic data of either cognitively normal individuals or patients with a confirmed diagnosis, and each predicting diagnostic data of one type from at least one other type; (c) producing a classification module that analyzes prediction errors to identify the best-fitting disease-specific cross-modal regression model and calculates disease probabilities; (d) assembling an ensemble model from the regression models and the classification module and deploying it at the computing device; (e) running the ensemble model to predict data, find the best-fitting model, calculate probabilities for different diagnoses, and output at least one diagnosis with the highest probability; and (f) selecting at least one treatment option from a stored list that is feasible for the output diagnosis. In other words, the claim uses a defined computational technique to improve the way a technological process is performed, rather than merely automating a preexisting mental judgment. Moreover, the ordered combination of (i) image-data preprocessing to generate brain- imaging features or radiomics data, (ii) cognitive-status-specific and therapeutic-response- specific cross-modal regression model generation with defined output metrics (predicted values, similarity scores, best-fit scores, and prediction errors), (iii) classification-module training using those metrics together with cognitive-status categories and therapeutic-response-class labels, (iv) ensemble-model assembly and application, and (v) a feedback unit for continuous model updating, is significantly more than any abstract idea of diagnosis or cognitive assessment.
The Applicant concludes that amended claim 1 "as a whole integrates the judicial exception into a practical application such that the claim is not directed to the judicial exception."
The Examiner disagrees since the Applicant’s arguments are not persuasive. The Examiner restates that claim 1 does not integrate the abstract idea into a practical application. Claim 1 does not recite additional elements that impose a meaningful limit on the abstract idea:
Claim 1: recites the following additional elements:
operating a computing system;
providing a machine-learning system and a computing device, wherein the computing device comprises a memory for storing reference subject datasets and a list of treatment options for each diagnosis, and a processing unit for running an ensemble model;
machine- learning system;
cross-modal regression models;
ensemble model;
classification module;
The additional elements as recited above amount to mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea. (refer to MPEP 2106.05(f)). Accordingly, the claim as a whole does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
In order to integrate the abstract idea into a practical application the additional elements should be shown to impose a meaningful limit on the abstract idea which is not the case in this invention. A colloquial interpretation of a practical application is not enough.
In order to integrate the abstract idea into a practical idea the Applicant could demonstrate at least one of the conditions enumerated below applies:
Improvements to the functioning of a computer, or to any other technology or technical field - see MPEP 2106.05(a)
Applying the judicial exception with, or by use of, a particular machine - see MPEP 2106.05(b)
Effecting a transformation or reduction of a particular article to a different state or thing - see MPEP 2106.05(c)
Applying or using 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 - see MPEP 2106.05(e) and Vanda Memo
The Applicant has not demonstrated any of the above listed conditions. As a result the Examiner restates the rejection of the invention under 35 USC §101.
Step 2B
Similar to the analysis under Step 2A Prong Two, the additional elements amount to mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea. (refer to MPEP 2106.05(f)). The use of generic computer components, in combination, do not perform functions that are not merely generic, and non-conventional even if the generic computer operations on a generic computing device is used to implement the abstract idea. Accordingly, the claim does not provide an inventive concept (significantly more than the abstract idea) and hence the claim is ineligible.
In order evaluate whether the claim recites additional elements that amount to an inventive concept what could be shown is:
Adding a specific limitation (unconventional other than what is well-understood, routine, conventional (WURC) activity in the field - see MPEP 2106.05(d)
The Applicant has not demonstrated the above listed condition.
For reasons of record and as set forth above, the examiner maintains the rejection of claims 1-11, 15, 17-18 as being directed to a judicial exception without significantly more, and thereby being directed to non-statutory subject matter under 35 USC §101. In reaching this decision, the Examiner considered all evidence presented and all arguments actually made by Applicant.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PIERRE L MACCAGNO whose telephone number is (571)270-5408. The examiner can normally be reached M-F 8:00 to 5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mamon Obeid can be reached at (571)270-1813. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PIERRE L MACCAGNO/Examiner, Art Unit 3687
/MAMON OBEID/Supervisory Patent Examiner, Art Unit 3687
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