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 .
Status of Claims
This action is in reply to the amendments and remarks filed on 08/06/2026.
Claims 1-4 and 6-9 are pending.
Claims 1-4 and 6-9 have been amended.
Claim 5 has been previously canceled.
Response to Arguments
Applicant’s arguments, with respect to the claim rejections of claim(s) 1-2 under 35 U.S.C. 112(b), have been considered but they are not persuasive. The applicant states the interface unit is “separate and distinct hardware”; however, the unit is maintained as passing the three-prong test for 112(f) analysis. Further, the applicant fails to point out where the unit is taught to be hardware in the specification; therefore, the previous 112(b) rejections regarding 112(f) interpretations are maintained.
A possible amendment for overcoming these interpretations and rejections could include “receiving input of a facial still image of an animal excluding a human”.
Applicant’s arguments, with respect to the rejection(s) of claim(s) 1-4 and 6-9 under 35 U.S.C. 101, have been considered but they are not persuasive. The applicant argues that the amended claims recite “additional elements that reflect the improvement identified in the specification. Therefore, in accordance with Ex parte Desjardins, Claim 1 and all associated dependent claims are directed to eligible subject matter” and practical application; and overcome the 101 rejections. The examiner respectfully disagrees.
The amendments and use in the claim do not operate to overcome the previous 101 abstract idea rejection. The claimed “deep learning model” remains claimed at a high level and performs black-box operations of merely “learning…training data”, and inputting and outputting types of data. The applicant points to Ex parte Desjardins decision for the abstract idea being directed toward a practical application, however these decisions explicitly state acceptable detail of an algorithm’s inner workings as to how neural networks layers influenced the outputs; thus, overcoming generally linking the use of the judicial exception to a particular technological environment or field of use.
The training operations and computer components are determined to be recited at a high level of generality and amount to 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; and the predicting, deep learning model, and premium calculation configuration are determined to be recited at a high level of generality, generally link the use of the judicial exception to a particular technological environment or field of use. See 35 U.S.C 101 section for full, updated analysis of claim limitations necessitated by applicant amendments.
Applicant is encouraged to add clarifying amendments to the deep learning model learning process and inner functions of the model, so the model is not merely performing black-box operations.
Applicant’s arguments, with respect to the rejection(s) of claims 1, 2, and 6 under 35 U.S.C. 103, have been considered and are persuasive. The previous rejections under 35 U.S.C. 103 have been withdrawn.
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:
“an interface unit that receives” in claims 1-2
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 § 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 1-4 and 7-9 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.
Claims 1-2’s limitations of “an interface unit that receives” invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Applicant’s specification pages 10-11 state “interface unit (communication unit) 30 includes a reception means 31 and an output means 32”; wherein page 5, lines 10-23 recite “reception means…is a means for receiving an input of a facial image…An image receiving method may be any method such as scanning, input of image data, and transmission”; page 8, lines 13-15 state “output by displaying, for example on the screen of a personal computer”; and Fig. 3 depicts the “interface unit” of a server. However, it is unclear to the examiner if the said interface unit is a set of instructions contained within a memory or if it is a separate and distinct hardware component that execute instructions to accomplish the claimed operations, and further if the “screen” is for the interface unit or the “terminal” being “a personal computer” on page 9, line 10. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claims so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
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 1-4 and 6-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1, 2, and 6 are respectively drawn to a system and method, hence each falls under one of four categories of statutory subject matter (Step 1). Nonetheless, the claims are directed to a judicially recognized exception of an abstract idea without significantly more.
Claims 1, 2, and 6 recite the following, or analogous, limitations “an interface unit that receives input of a facial still image of an animal excluding a human [preparing a facial still image of an animal excluding a human claim 6]; [and inputting the facial image to a…model claim 6];…inputs the facial still image of the animal, and outputs a predictive assessment, based on the facial still image and the training data, that the animal will contract the future occurrence of the ophthalmic, an otological, or a dermatological disease within one or more years from a time of imaging the facial still image”. These limitations, as claimed, under its broadest reasonable interpretation, can be evaluated in a human mind, except for the recitation of generic computer components. Other than reciting “a computer”, “to a computer including artificial intelligence as training data and making the artificial intelligence learn the data”, “a processor that predicts a future occurrence of an ophthalmic, an otological, or a dermatological disease of the animal using a deep learning model”, “deep learning model”, “wherein the deep learning model performs learning by using facial still images of animals excluding humans and a presence of the ophthalmic, an otological, or a dermatological disease in the animals within a predetermined period from the time of imaging the animals, which is obtained from pet insurance claim records for the animals, as training data; the deep learning model…”, and “a premium calculation processor that calculates an insurance premium for the animal, based on the predictive assessment, and is configuring the output the insurance premium for the animal [claim 2]”, to perform the exceptions, nothing in the claims preclude the steps from practically being performed in the human mind. For example, a human expert can:
mentally/with the aid of pen and paper an interface unit that receives input of a facial still image of an animal excluding a human [preparing a facial still image of an animal excluding a human claim 6] (e.g. by thinking of/writing out remembering a photo of a dog’s face),
mentally/with the aid of pen and paper and inputting the facial image to a…model [claim 6] (e.g. by thinking of/writing out a first calculation with parameters to segment the remembered photo of the dog’s face and calculate a probability that type of dog will contract an illness within a certain number of years),
mentally/with the aid of pen and paper …inputs the facial still image of the animal, and outputs a predictive assessment, based on the facial still image and the training data, that the animal will contract the future occurrence of the ophthalmic, an otological, or a dermatological disease within one or more years from a time of imaging the facial still image (e.g. by thinking of/writing out a first calculation with parameters to segment the remembered photo of the dog’s face and calculate a probability that type of dog will contract a skin illness within a certain number of years).
Thus, the claims recite a mental process (Step 2A, Prong 1).
Claims 1, 2, and 6 include additional elements, “a computer”, “to a computer including artificial intelligence as training data and making the artificial intelligence learn the data”, “a processor that predicts a future occurrence of an ophthalmic, an otological, or a dermatological disease of the animal using a deep learning model”, “deep learning model”, “wherein the deep learning model performs learning by using facial still images of animals excluding humans and a presence of the ophthalmic, an otological, or a dermatological disease in the animals within a predetermined period from the time of imaging the animals, which is obtained from pet insurance claim records for the animals, as training data; the deep learning model…”, and “a premium calculation processor that calculates an insurance premium for the animal, based on the predictive assessment, and is configuring the output the insurance premium for the animal [claim 2]”, however the recitations of these elements are at a high level of generality and adding the words “apply it” (or an equivalent) with the judicial exception (i.e., “to a computer including artificial intelligence as training data and making the artificial intelligence learn the data”, and “wherein the deep learning model performs learning by using facial still images of animals excluding humans and a presence of the ophthalmic, an otological, or a dermatological disease in the animals within a predetermined period from the time of imaging the animals, which is obtained from pet insurance claim records for the animals, as training data; the deep learning model…”), or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (i.e., “a computer” and “a processor”, and “a premium calculation processor”) (see MPEP 2106.05(f)); and generally linking the user of the judicial exception to a particular technological environment or field of use (i.e., “predicts a future occurrence of an ophthalmic, an otological, or a dermatological disease of the animal using a deep learning model” and “deep learning model”, “calculates an insurance premium for the animal, based on the predictive assessment, and is configuring the output the insurance premium for the animal”) (see MPEP 2106.05(h)); and amount to mere data gathering, storing, or outputting which are forms of adding insignificant extra-solution activity to the judicial exception (i.e., “capable of outputting the insurance premium for the animal, excluding humans applying for pet insurance”) (see MPEP 2106.05(g)),. Hence, each of the additional limitations or in combination do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea (Step 2A, Prong 2). The additional elements in the claim do not amount to significantly more than an abstract idea. Furthermore, 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 the integration of the abstract idea into a practical application, the additional elements of using “a computer”, “to a computer including artificial intelligence as training data and making the artificial intelligence learn the data”, “a processor that predicts a future occurrence of an ophthalmic, an otological, or a dermatological disease of the animal using a deep learning model”, “deep learning model”, “wherein the deep learning model performs learning by using facial still images of animals excluding humans and a presence of the ophthalmic, an otological, or a dermatological disease in the animals within a predetermined period from the time of imaging the animals, which is obtained from pet insurance claim records for the animals, as training data; the deep learning model…”, and “a premium calculation processor that calculates an insurance premium for the animal, based on the predictive assessment, and is configuring the output the insurance premium for the animal [claim 2]”, to perform the steps of the independent claims amounts to no more than mere 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; generally linking the user of the judicial exception to a particular technological environment or field of use; and amount to mere data gathering, storing, or outputting which are forms of adding insignificant extra-solution activity to the judicial exception; as these cannot provide an inventive concept. (STEP 2B). As such, claims 1, 2, and 6 are not patent eligible.
Dependent claims 3-4 and 7-9 are also ineligible for the same reasons given with respect to claims 1, 2, and 6. The dependent claims describe additional mental processes:
mentally/with the aid of pen and paper wherein the input still image is an image obtained by imaging the face of the animal from the front of the animal (claims 3 and 7) (e.g. by mentally/writing out the remembered photo is of a dog’s face looking into the remembered camera)
mentally/with the aid of pen and paper inputting a facial image of an animal to be in coverage of insurance…and…determining an insurance fee of the animal in accordance with the predictive assessment (claims 4 and 8-9) (e.g. by mentally/writing out a second calculation for outputting an health insurance premium for the dog based on the first calculation’s probability)
Again, the dependent claims continued to cover the performance of the limitation in the mind as inherited from the independent claims (Step 2A, Prong 1). The dependent claim 4 and 8-9’s recitation of “an insurance fee calculation system” and “to the system according to claim 1 [2 or 3]”, is recited at a high level and amount to 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 (see MPEP 2106.05(f)), and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea (Step 2A, Prong 2). The additional element in the claims do not amount to significantly more than an abstract idea. As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements to perform the steps of in the dependent claims and perform the steps of the claims amount 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; and these cannot provide an inventive concept. (STEP 2B). As such, dependent claims 3-4 and 7-9 additional elements or combination of elements do not amount to significantly more than an abstract idea nor provide any inventive concept, nor impose a meaningful limit to integrate the elements into a practical application or significantly more than the judicial exceptions; therefore, the dependent claims are not deemed patent eligible.
Allowable Subject Matter
The following is a statement of reasons for the indication of allowable subject matter: Claims 1-4 and 6-9 are deemed allowable over prior art due to analogously reciting (or due to their dependency) “presence of the ophthalmic, otological, or dermatological disease in the animals within a predetermined period from a time of imaging the animals which is obtained from pet insurance claim records for the animals, as training data”, and predicting a future occurrence of the disease “within predetermined period one or more years from a time of imaging the facial still image”
Kojima et al (US Pub 20140316216), is deemed the closest art found that teaches neural network matching data for estimating an animal’s disease for a specific time, including “the disease is dermatitis, in the second database 52, ‘SCRATCHED SKIN’ is stored as the name of the affected part, and the specific affected part image of ‘HAIR FALLS OUT AND SKIN IS RED’ is stored in the image of ‘SCRATCHED SKIN’” [paragraphs 0054-0055, 0062-0063, and 0083-0093]. However, Kojima et al does not explicitly teach predicting a future occurrence of a disease, from the time of imaging, within a certain amount of time with a model trained on like occurrences from insurance claim records the same way required by the claim.
Gibbs et al (US Pub 20200381119) hereinafter Gibbs, teaches a machine learning engine able to diagnose animal behavior anomalies, contacting medical resources and determining future occurrences of the anomalies [paragraphs 0055, 0065, 0070, 0075, 0092-0093, and Figs. 7 and 15]. However, Gibbs et al does not explicitly teach predicting a future occurrence of a disease, from the time of imaging, within a certain amount of time with a model trained on like occurrences from insurance claim records the same way as required by the amended claim limitations.
Hayward et al (US Pub 20210256615) hereinafter Hayward, teaches deep learning of predicting likelihood of various medical related conditions for insurance purposes “within some future time horizon” [paragraphs 0021-0022, 0059, 0102, 0104, 0109, and 0112]. However, Hayward et al does not explicitly teach predicting a future occurrence of a disease, from the time of imaging, within a certain amount of time with a model trained on like occurrences from insurance claim records the same way as required by the amended claim limitations.
Leong et al (US Pub 20200159720) hereinafter Leong, teaches machine learning model for image analysis and feature recognition of animal features [paragraphs 0031-0033]. However, Choudhury et al does not explicitly teach predicting a future occurrence of a disease, from the time of imaging, within a certain amount of time with a model trained on like occurrences from insurance claim records the same way as required by the amended claim limitations.
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.
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 extension fee 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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/C.M./Examiner, Art Unit 2123
/ALEXEY SHMATOV/Supervisory Patent Examiner, Art Unit 2123
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