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 .
Applicant filed a communication dated 10/11/2024 in which claims 1-15 are pending in the application.
Claim Objections
Claims 1-14 are objected to because of the following informalities: In claims 1 and 8, it is unclear where the preamble ends and the steps/structure of the claim start. Based on the independent claim 15 which is substantially similar to claims 1 and 8, Examiner interprets that the preamble of claims 1 and 8 is recited in lines 1-6 and the body of the claim starts with line 7. However, Examiner recommends using the word “comprising” or equivalent similar to what is present in claim 15 to indicate a separation of preamble from the body of the claim.
Claim Rejections - 35 USC § 112
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 1-7 are 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 1 recites the limitation "the first and the second” in line 9. There is insufficient antecedent basis for this limitation in the claim.
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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of extracting an oriental medicine based on diagnosis of a patient without significantly more.
Examiner has identified claim 1 as the claim that represents the claimed invention presented in independent claims 1, 8, and 15.
Claim 1 is directed to a system, which is one of the statutory categories of invention (Step 1: YES).
The claim 1 describes an oriental medicine diagnosis and prescription system wherein a deep learning model learned using at least one of information on an oriental medicine formulation mapped to a symptom constituting a proof of evidence and at least one of information on a personality type mapped to a constitutional type is utilized, wherein the oriental medicine diagnosis and prescription system includes an artificial neural network based on a deep learning model which extracts the first and the second feature vectors from a user's questionnaire response data, receives the feature vectors as an input layer to extract at least one candidate oriental medicine formulation, sorts the extracted candidate oriental medicine formulations according to prescription priorities, or receives the second feature vector as an input layer to determine at least one health constitution type, and outputs health information mapped with the determined health constitution type; and wherein the first feature vector includes information related to a cumulative score or probability value for a disease symptom of the user and symptoms constituting diagnosis mapped to the candidate oriental medicine formulation, and wherein the second feature vector includes health information related to a health constitution type of the user. These limitations (with the exception of italicized limitations) describe the abstract idea of extracting an oriental medicine based on diagnosis of a patient which may correspond to a certain method of organizing human activity and thus the claim recites an abstract idea. The additional elements of a deep learning model, diagnosis and prescription system, an artificial neural network do not restrict the claim from reciting an abstract idea. Thus, the claim 1 recites an abstract idea (Step 2A, Prong One: YES).
This judicial exception is not integrated into a practical application because the additional elements of a deep learning model, diagnosis and prescription system, an artificial neural network result in no more than simply applying the abstract idea using generic computer elements. The additional elements of a deep learning model, diagnosis and prescription system, an artificial neural network are recited at a high level of generality and under their broadest reasonable interpretation comprises a generic computer arrangement. The presence of a generic computer arrangement is nothing more than to implement the claimed invention by applying the exception using a generic computer element (MPEP 2106.05(f)). Therefore, the recitations of additional elements do not meaningfully apply the abstract idea and hence do not integrate the abstract idea into a practical application. Thus, the claim 1 is directed to an abstract idea (Step 2A-Prong 2: NO).
The claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claim recites the additional elements of a deep learning model, diagnosis and prescription system, an artificial neural network are recited at a high level of generality in that it result in no more than simply applying the abstract idea using generic computer elements. The additional elements when considered separately and as an ordered combination do not amount to add significantly more as these elements provide nothing more than to simply apply the exception in a generic computer environment (Step 2B: NO). Thus, the claim 1 is not patent eligible.
Similar arguments can be presented for other independent claims 8 and 15 and hence these claims are rejected on similar grounds as claim 20.
Dependent claims 2-7 and 9-14 further define the abstract idea that is present in the independent claims 1 and 8, thus correspond to a certain method of organizing human activity, and hence are abstract in nature for the reason presented above. Dependent claims do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Therefore, the claims 1-15 are not patent-eligible.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-15 are rejected under 35 U.S.C. 103 as being unpatentable over Bostic et al., US Patent Application No. 2021/0225520 in view of Jeon, KR 10-2044079 B1.
Regarding claim 1, Bostic discloses an oriental medicine diagnosis and prescription system wherein a deep learning model learned using at least one of information on an oriental medicine formulation mapped to a symptom constituting a proof of evidence and at least one of information on a personality type mapped to a constitutional type is utilized ([0047], [0049], machine learning neural network model, [0172]),
wherein the oriental medicine diagnosis and prescription system includes an artificial neural network based on a deep learning model which extracts the first and the second feature vectors from a user's questionnaire response data, receives the feature vectors as an input layer to extract at least one candidate oriental medicine formulation, sorts the extracted candidate oriental medicine formulations according to prescription priorities, or receives the second feature vector as an input layer to determine at least one health constitution type, and outputs health information mapped with the determined health constitution type ([0047], [0049], [0272], report as output); and
wherein the first feature vector includes information related to a cumulative score or probability value for a disease symptom of the user and symptoms constituting diagnosis mapped to the candidate oriental medicine formulation ([0047], [0049], [0052] risk score), and
wherein the second feature vector includes health information related to a health constitution type of the user ([0272]).
Bostic does not specifically disclose
oriental medicine and
sorts the extracted candidate oriental medicine formulations according to prescription priorities.
However, Jeon discloses
oriental medicine ([0009], [0054]) and
sorts the extracted candidate oriental medicine formulations according to prescription priorities ([0041]-[0042], filter).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the above-noted disclosure of Bostic to include the above-noted disclosure of Jeon. The motivation for combining these references would have been to recommend an oriental medicine.
Regarding claim 2, Bostic discloses wherein the artificial neural network comprises:
a first artificial neural network which outputs at least one candidate oriental medicine formulation defined by at least one oriental medicine substance corresponding to the questionnaire response of the user, and a combination of the at least one oriental medicine substance ([0039], [0049], [0172]); and
a second artificial neural network which receives the candidate oriental medicine formulation output from the first neural network, accumulates questionnaire response scores related to symptoms constituting the proof of evidence mapped to the candidate oriental medicine formulation, calculates a corresponding accumulated score or probability value of the symptom constituting the proof of evidence, and deletes the symptom constituting the proof of evidence mapped to the candidate oriental medicine formulation, so that the mapping relationship between the candidate oriental medicine formulation and the proof of evidence updates if the corresponding accumulated score or probability value of the symptom constituting a proof of evidence is lower than a threshold value, and determines a prescription priority of the candidate oriental medicine formulation in consideration of the updated mapping relationship ([0047], [0049], [0216], [0231], [0272]).
However, Jeon discloses
oriental medicine ([0009], [0054]).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the above-noted disclosure of Bostic to include the above-noted disclosure of Jeon. The motivation for combining these references would have been to recommend an oriental medicine.
Regarding claim 3, Bostic discloses wherein the second artificial neural network maintains the mapping relationship between the candidate oriental medicine formulation and the symptom without updating if the cumulative score or probability value of the symptom constituting the proof of evidence is greater than or equal to a threshold value ([0216], [0231]).
However, Jeon discloses
oriental medicine ([0009], [0054]) and
sorts the extracted candidate oriental medicine formulations according to prescription priorities ([0041]-[0042], filter).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the above-noted disclosure of Bostic to include the above-noted disclosure of Jeon. The motivation for combining these references would have been to recommend an oriental medicine.
Regarding claim 4, Jeon discloses wherein determining the prescription priority of the candidate oriental medicine formulations includes:
a first sorting based on the symptoms which determine a grade among symptoms constituting the proof of evidence mapped to the candidate oriental medicine formulations ([0041]-[0042]), and
a second sorting based on the symptoms which determine a rank among symptoms constituting the proof of evidence mapped to the candidate oriental medicine formulations in the same grade ([0041]-[0042]).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the above-noted disclosure of Bostic to include the above-noted disclosure of Jeon. The motivation for combining these references would have been to recommend an oriental medicine.
Regarding claim 5, Bostic discloses
wherein the symptom constituting the proof of evidence includes any one of symptoms of an essential symptom, a frequent symptom, a probable symptom, tendency and an improper symptom ([0064]),
wherein the essential symptom, the frequent symptom, and the improper symptom are used as criteria for determining a rank, and the probable symptom, and tendency are used as criteria for determining a rank in the same grade ([0064]).
Regarding claim 6, Bostic discloses wherein the artificial neural network further includes a third artificial neural network which outputs health information corresponding to the determined health constitution type by referring to a mapping table between the health constitution type and health information ([0047], one or more relationships, [0049], [0272], matching).
Regarding claim 7, Bostic discloses
wherein the constitution type includes n types determined from a combination of temperature, eating, excretion, and mental ([0272]),
wherein the health information includes at least one or more of information about your constitution, information about your current health status and predicted diseases (unforeseen diseases), information about your health by life cycle, information about your health by time zone of the day, information about your biorhythm, information about your body type (outward appearance), information about your personality (inward appearance), information about food and nutritional supplements, information about exercise, and information about music ([0272].
Regarding claim 9, Bostic discloses wherein the command further includes a command for determining at least one constitution type based on a third feature vector among above feature vectors, and outputting at least one personality type mapped to the determined constitution type ([0272]).
Regarding claim 10, Bostic discloses wherein the command for determining at least one candidate oriental medicine formulation based on the first feature vector among the feature vectors includes outputting at least one or more candidate oriental medicine formulations defined by a combination of at least one oriental medicine substance corresponding to the user's questionnaire response and at least the one oriental medicine substance ([0047], [0049], [0272]).
However, Jeon discloses
oriental medicine ([0009], [0054]).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the above-noted disclosure of Bostic to include the above-noted disclosure of Jeon. The motivation for combining these references would have been to recommend an oriental medicine.
Claims 8 and 11-15 are substantially similar to claims 1-4 and 7 and hence rejected on similar grounds.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure are listed on the attached PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RAJESH KHATTAR whose telephone number is (571)272-7981. The examiner can normally be reached M-F 8AM-5PM.
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, Shahid Merchant can be reached at 571-270-1360. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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RAJESH KHATTAR
Primary Examiner
Art Unit 3684
/RAJESH KHATTAR/Primary Examiner, Art Unit 3684