DETAILED ACTION
Claims 1-5 & 7-10 are currently pending and have been examined.
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 1-5 & 7-10 are rejected under 35 U.S.C. §101 because the claimed invention is directed to an abstract idea without significantly more.
Subject Matter Eligibility Criteria - Step 1:
Claims 1-5, 7, & 9-10 are directed to a system (i.e., a machine); Claim 8 is directed to a method (i.e., a process). Accordingly, Claims 1-5 & 7-10 are all within at least one of the four statutory categories.
Subject Matter Eligibility Criteria - Alice/Mayo Test: Step 2A - Prong One:
Regarding Prong One of Step 2A, the claim limitations are to be analyzed to determine whether, under their broadest reasonable interpretation, they “recite” a judicial exception or in other words whether a judicial exception is “set forth” or “described” in the claims. MPEP 2106.04(II)(A)(1). An “abstract idea” judicial exception is subject matter that falls within at least one of the following groupings: a) certain methods of organizing human activity, b) mental processes, and/or c) mathematical concepts. MPEP 2106.04(a).
Representative independent claim 1 includes limitations that recite at least one abstract idea. Specifically, independent claim 1 recites:
1. An asthmatic disease condition estimation server comprising:
a storage configured to store a plurality of clusters into which patients with asthma are classified, and a plurality of disease conditions of asthma associated with each cluster;
a reception unit configured to receive symptom information indicating a symptom of a subject;
a determination unit configured to identify the cluster to which the subject belongs among the plurality of clusters, based on the symptom information, and identify the disease condition stored in the storage in association with the identified cluster; and
an output unit configured to output the identified disease condition as a predicted disease condition of the subject;
wherein the reception unit is configured to receive identification information for identifying the subject, together with the symptom information, wherein
the storage is configured to store the identification information and the symptom information in association with each other,
store, each time the symptom information of the subject is received, the symptom information as time-series symptom information of the subject, and
the determination unit is configured to identify the cluster for each of the plurality of pieces of the time- series symptom information of the subject,
identify, as a predicted cluster, the cluster to which the subject is predicted to belong, based on the plurality of clusters each identified for each piece of the time-series symptom information, and
identify, as a predicted disease condition, the disease condition stored in the storage in association with the predicted cluster.
The Examiner submits that the foregoing underlined limitations constitute “methods of organizing human activity” because storing patient data including cluster, disease, and symptom data, detecting a medical condition, generating and sending a notification are associated with managing personal behavior or relationships or interactions between people. For example, but for the system, this claim encompasses a person facilitating data access, receiving data, and outputting data in the manner described in the identified abstract idea. The Examiner notes that “method of organizing human activity” includes a person’s interaction with a computer – see MPEP 2106.04(a)(2)(II)(C). If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or interactions between people but for the recitation of generic computer components, then it falls within the “method of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Accordingly, independent claim 1 and analogous independent claim 8 recite at least one abstract idea.
Furthermore, dependent claims 2-7 further narrow the abstract idea described in the independent claims. Claims 2 & 6 recite the cluster and disease information, Claim 3 recites receiving questionnaire data. These limitations only serve to further limit the abstract idea and hence, are directed towards fundamentally the same abstract idea as independent claim 1 and analogous independent claim 8, even when considered individually and as an ordered combination.
Subject Matter Eligibility Criteria - Alice/Mayo Test: Step 2A - Prong Two:
Regarding Prong Two of Step 2A of the Alice/Mayo test, it must be determined whether the claim as a whole integrates the abstract idea into a practical application. As noted at MPEP §2106.04(II)(A)(2), it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.” MPEP §2106.05(I)(A).
In the present case, the additional limitations beyond the above-noted at least one abstract idea recited in the claim are as follows (where the bolded portions are the “additional limitations” while the underlined portions continue to represent the at least one “abstract idea”):
1. An asthmatic disease condition estimation server comprising:
a storage configured to store a plurality of clusters into which patients with asthma are classified, and a plurality of disease conditions of asthma associated with each cluster;
a reception unit configured to receive symptom information indicating a symptom of a subject;
a determination unit configured to identify the cluster to which the subject belongs among the plurality of clusters, based on the symptom information, and identify the disease condition stored in the storage in association with the identified cluster; and
an output unit configured to output the identified disease condition as a predicted disease condition of the subject;
wherein the reception unit is configured to receive identification information for identifying the subject, together with the symptom information, wherein
the storage is configured to store the identification information and the symptom information in association with each other,
store, each time the symptom information of the subject is received, the symptom information as time-series symptom information of the subject, and
the determination unit is configured to identify the cluster for each of the plurality of pieces of the time- series symptom information of the subject,
identify, as a predicted cluster, the cluster to which the subject is predicted to belong, based on the plurality of clusters each identified for each piece of the time-series symptom information, and
identify, as a predicted disease condition, the disease condition stored in the storage in association with the predicted cluster.
For the following reasons, the Examiner submits that the above identified additional limitations do not integrate the above-noted at least one abstract idea into a practical application.
Regarding the additional limitations of the storage, reception unit, determination unit, and output unit; the Examiner submits that these limitations amount to merely using computers as tools to perform the above-noted at least one abstract idea (see MPEP § 2106.05(f)).
Regarding the additional limitation of sending the workflow to the storage system for storage with images as part of the exam, the Examiner submits that this additional limitation merely adds extra-solution activity (data gathering; selecting data to be manipulated) to the at least one abstract idea in a manner that does not meaningfully limit the at least one abstract idea (see MPEP § 2106.05(g)) and is conventional as it merely consists of transmitting data over a network (see MPEP § 2106.05(d)(II)).
Thus, taken alone, the additional elements do not integrate the at least one abstract idea into a practical application.
Looking at the additional limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole with the abstract idea, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole does not integrate the abstract idea into a practical application of the abstract idea. MPEP §2106.05(I)(A) and §2106.04(II)(A)(2).
For these reasons, representative independent claim 1 and analogous independent claim 8 do not recite additional elements that integrate the judicial exception into a practical application.
Accordingly, the claims recites at least one abstract idea.
The remaining dependent claim limitations not addressed above fail to integrate the abstract idea into a practical application as set forth below:
Claim 5: These claims recite training data and using a machine learning model, the Examiner submits that these additional claim limitations amount to an attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result and is equivalent to the words “apply it”. See MPEP 2106.05(f)(1).
Thus, taken alone, any additional elements do not integrate the at least one abstract idea into a practical application. Therefore, the claims are directed to at least one abstract idea.
Subject Matter Eligibility Criteria - Alice/Mayo Test: Step 2B:
Regarding Step 2B of the Alice/Mayo test, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for reasons the same as those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application.
As discussed above, regarding the additional limitation of sending the workflow to the storage system for storage with images as part of the exam, the Examiner submits that this additional limitation merely adds extra-solution activity (data gathering; selecting data to be manipulated) to the at least one abstract idea in a manner that does not meaningfully limit the at least one abstract idea (see MPEP § 2106.05(g)) and is conventional as it merely consists of transmitting data over a network (see MPEP § 2106.05(d)(II)).
The dependent claims also do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the dependent claims do not integrate the at least one abstract idea into a practical application.
Therefore, claims 1-5 & 7-10 are ineligible under 35 USC §101.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: reception unit, determination unit, and output unit in claims 1-5 & 9-10.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1 & 7-9 are rejected under 35 U.S.C. 103 as being unpatentable over Koch (US20220172841) in view of Choi (US20140073882).
As per claim 1, Koch teaches an asthmatic disease condition estimation server comprising:
a storage configured to store a plurality of clusters into which patients with asthma are classified, and a plurality of disease conditions of asthma associated with each cluster (para. 14-20, 47-48: expert medical logic, entered into the system, is a database of rules providing specific logic how to classify subjects retrospectively, based on the data provided; chronic conditions including asthma can be determined);
a reception unit configured to receive symptom information indicating a symptom of a subject (para. 45: new patient data input into system);
a determination unit configured to identify the cluster to which the subject belongs among the plurality of clusters, based on the symptom information, and identify the disease condition stored in the storage in association with the identified cluster (para. 61: cluster of diseases that have overlapping clinical presentations to define a differential diagnosis, or list of possible disease diagnoses based on the clinical presentation. Risk factors for a given disease in the differential diagnosis are determined for each patient based on at least some of the patient's gender, age, genetic background, history of medications, family history, and for women, gynecological history); and
an output unit configured to output the identified disease condition as a predicted disease condition of the subject (para. 24: system provides explanatory output regarding relevant symptoms and signs, and analyzes trends, symptom recurrence, symptom distribution and all relevant patient history, to determine the risk of the particular subject having or developing the specific disease under consideration by the system);
store, each time the symptom information of the subject is received, the symptom information as time-series symptom information of the subject (para. 45: historical patient data is collected from electronic medical records (EMR), electronic health records (EHR), insurance claims data, or data from other sources, such as symptoms), and
the determination unit is configured to identify the cluster for each of the plurality of pieces of the time- series symptom information of the subject (para. 91: new subjects' data points, shown as empty dots, appear throughout the parameter range and cluster together with similar subjects from the training set, so the classifier algorithm is able to use the clustering to suggest the correct diagnosis for such patients. The transformation of the feature vectors into the embedding space allows the system to predict or diagnose an individual at risk of a given autoimmune disease by placing this subject close to others with similar parameter values, i.e., sharing the same signs, symptoms, and other diagnostic criteria),
identify, as a predicted cluster, the cluster to which the subject is predicted to belong, based on the plurality of clusters each identified for each piece of the time-series symptom information (para. 91: new subjects' data points, shown as empty dots, appear throughout the parameter range and cluster together with similar subjects from the training set, so the classifier algorithm is able to use the clustering to suggest the correct diagnosis for such patients. The transformation of the feature vectors into the embedding space allows the system to predict or diagnose an individual at risk of a given autoimmune disease by placing this subject close to others with similar parameter values, i.e., sharing the same signs, symptoms, and other diagnostic criteria), and
identify, as a predicted disease condition, the disease condition stored in the storage in association with the predicted cluster (para. 91: classifier algorithm is able to use the clustering to suggest the correct diagnosis for such patients).
Koch does not expressly teach wherein the reception unit is configured to receive identification information for identifying the subject, together with the symptom information, wherein the storage is configured to store the identification information and the symptom information in association with each other.
Choi, however, teaches to using clustering for patient diagnosis where patient data including demographic and historical data is stored with symptom data in a database (para. 65).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the aforementioned features in Choi with Koch based on the motivation of collecting and authoring medical diagnosis information for performing precise determinations of patient diseases (Choi – para. 5).
Claims 7-8 recite substantially similar limitations as those already addressed in claim 1, and, as such, are rejected for similar reasons as given above.
As per claim 9, Koch and Choi teach the asthmatic disease condition estimation server according to claim 1. Koch teaches wherein the determination unit is configured to identify, as a predicted cluster, the cluster to which the subject is predicted to belong, based on a transition between the plurality of clusters each identified for each piece of the time-series symptom information (para. 92: Individuals who have been screened and have a probability of a specific diagnosis that is above normal but fails to reach threshold can be monitored with additional visits to follow the course of signs and symptoms over time, to determine whether the threshold is reached that would transfer the individual from the normal group to the treatment group.).
Prior Art Rejection
All of the cited references fail to expressly teach or suggest, either alone or in combination, the features found within dependent claims 2-5 & 10. In particular, the cited prior art of record fails to expressly teach or suggest the combination of:
wherein the plurality of disease conditions includes airway inflammation, and airflow obstruction, and the plurality of clusters includes an airway inflammation cluster associated with only the airway inflammation of the airway inflammation and the airflow obstruction, an airflow obstruction cluster associated with only the airflow obstruction of the airway inflammation and the airflow obstruction, and an all-disease condition cluster associated with both of the airway inflammation and the airflow obstruction & further comprising a plotting unit configured to plot, on a UMAP plot, the plurality of pieces of the time-series symptom information of the subject as cases of the subject, wherein the determination unit is configured to identify, as the predicted cluster, the cluster to which the subject is predicted to belong, based on a trajectory of the cases of the subject on the UMAP plot, plotted by the plotting unit.
The most relevant prior art of record includes:
Koch (US20220172841) teaches to enabling prediction, screening, early diagnosis, and recommended intervention or treatment selection of chronic medical conditions using artificial intelligence operating in conjunction with large medical datasets. Borsody (US20210321932) teaches to evaluate one or more patient data inputs relating to a first specific disease, compare the one or more data inputs to a set of values from at least one database using at least one computational algorithm, train the at least one computational algorithm for estimating a diagnosis of the patient based on the first specific disease, determine a first diagnostic score for the patient for the specific disease using the at least one computational algorithm, diagnose the patient as having the specific disease when the first diagnostic score for the first specific disease is above a first value, and provide the diagnosis for the patient as an output.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jonathan K Ng whose telephone number is (571)270-7941. The examiner can normally be reached M-F 8 AM - 5 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, Anita Coupe can be reached at 571-270-7949. 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.
/Jonathan Ng/ Primary Examiner, Art Unit 3619
Prosecution Insights