DETAILED ACTION
Status of Claims
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is in reply to a response filed 25 February 2026, on an application filed on 15 September 2023.
Claims 1, 9, 17, 21 and 22 have been amended.
Claims 1-13 and 15-22 are currently pending and have been examined.
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.
Use of the word “means” (or “step for”) in a claim with functional language creates a rebuttable presumption that the claim element is to be treated in accordance with 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph). The presumption that 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph) is invoked is rebutted when the function is recited with sufficient structure, material, or acts within the claim itself to entirely perform the recited function.
Absence of the word “means” (or “step for”) in a claim creates a rebuttable presumption that the claim element is not to be treated in accordance with 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph). The presumption that 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph) is not invoked is rebutted when the claim element recites function but fails to recite sufficiently definite structure, material or acts to perform that function.
Claim elements in this application that use the word “means” (or “step for”) are presumed to invoke 35 U.S.C. 112(f) except as otherwise indicated in an Office action. Similarly, claim elements that do not use the word “means” (or “step for”) are presumed not to invoke 35 U.S.C. 112(f) except as otherwise indicated in an Office action.
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: analytics module configured to analyze in claims 1, 9, 17 and 21.
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 limitation analytics module configured to analyze has/have been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because it uses/they use a generic placeholder module coupled with functional language configured to analyze without reciting sufficient structure to achieve the function. Furthermore, the generic placeholder is not preceded by a structural modifier.
Since the claim limitation(s) invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, claims 1, 9, 17 and 21 has/have been interpreted to cover the corresponding structure described in the specification that achieves the claimed function, and equivalents thereof.
A review of the specification shows that the following appears to be the corresponding structure described in the specification for the 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph limitation: there is no specific support in the specification.
If applicant wishes to provide further explanation or dispute the examiner’s interpretation of the corresponding structure, applicant must identify the corresponding structure with reference to the specification by page and line number, and to the drawing, if any, by reference characters in response to this Office action.
If applicant does not intend to have the claim limitation(s) treated under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112 , sixth paragraph, applicant may amend the claim(s) so that it/they will clearly not invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, or present a sufficient showing that the claim recites/recite sufficient structure, material, or acts for performing the claimed function to preclude application of 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
For more information, see MPEP § 2173 et seq. and Supplementary Examination Guidelines for Determining Compliance With 35 U.S.C. 112 and for Treatment of Related Issues in Patent Applications, 76 FR 7162, 7167 (Feb. 9, 2011).
Claim Rejections - 35 USC § 112
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.
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.
Claims 1-13 and 15-22 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), as being indefinite for failing to particularly point out and distinctly claim the subject matter which applicant regards as the invention.
Claims 1, 9, 17 and 21 recite the limitation an analytics module configured to analyze the PDT risk level and the pet data to determine an analysis statement for a user type in the transmitting limitation. Claim limitation an analytics module configured to analyze invokes 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. Nothing in the claim or specification indicates what the analytics module is comprised of. 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 claim 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.
To the extent that other claims rely on claims that are rejected under 35 USC 112 and fail to correct the deficiencies of the claims they rely on, those other claims are rejected for the same reasons as the claims they rely on. Appropriate correction is required.
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 1-13 and 15-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1
Claims 1-13 and 15-22 are within the four statutory categories. Claims 1-8, 21 and 22 are drawn to a computer-implemented method for predicting a risk level for the presence of persistent deciduous teeth (PDT) for one or more pets, which is within the four statutory categories (i.e. process). Claims 8-13, 15 and 16 are drawn to a computer system for predicting a risk level for the presence of persistent deciduous teeth (PDT) for one or more pets, which is within the four statutory categories (i.e. machine). Claims 17-20 are drawn to a non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform operations for predicting a risk level for the presence of persistent deciduous teeth (PDT) for one or more pets, which is within the four statutory categories (i.e. manufacture).
Prong 1 of Step 2A
Claim 1 recites: A computer-implemented method for predicting a risk level for the presence of persistent deciduous teeth (PDT) for one or more pets, the computer-implemented method comprising:
receiving, by one or more processors, pet image data corresponding to a unique pet identifier from a user device and a pet information database, the pet image data including one or more pet attributes, wherein the one or more pet attributes include one or more PDT biomarkers corresponding to a PDT genetic predisposition of a pet corresponding to the unique pet identifier;
inputting, by the one or more processors, the one or more pet attributes into a trained machine-learning model that is configured to output a result value indicating a PDT probability weight for each of the one or more pet attributes;
utilizing, by the one or more processors, a PDT risk level prediction algorithm to select one or more similar pet datasets based on the one or more pet attributes including the one or more PDT biomarkers, wherein each of the one or more similar pet datasets includes a corresponding PDT risk level;
inputting, by the one or more processors, the result value for each of the one or more pet attributes and the result value for each of the one or more similar pet datasets into a logistic regression machine-learning model that is configured to determine and output a PDT risk level;
receiving, by the one or more processors, pet data associated with the pet from one or more pet information databases, wherein the pet data includes a pet veterinarian interaction frequency;
transmitting, by the one or more processors, the PDT risk level and the pet data to an analytics module configured to analyze the PDT risk level and the pet data to determine an analysis statement for a user type, wherein the user type includes a pet owner or a veterinarian;
determining, by the one or more processors, one or more recommendations based on the PDT risk level, wherein the one or more recommendations include identifying at least one tooth for removal; and
displaying, by the one or more processors, the PDT risk level, the analysis statement and the one or more recommendations on one or more user interfaces of the user device.
Claim 21 recites the limitations presented in claim 1, but also adds:
displaying, by the one or more processors, … a corresponding intervention, wherein the intervention includes recommending the removal of one or more teeth in order to decrease the risk of periodontal disease that could be a consequence of PDT.
The underlined limitations as shown above, given the broadest reasonable interpretation, cover the abstract ideas of certain method of organizing human activity because they recite managing personal behavior or relationships or interactions between people (i.e. social activities, teaching, and following rules or instructions - in this case, the steps of determining a PDT weight based on a pet attribute and then a PDT risk based on the PDT weight, and providing a corresponding intervention), e.g. see MPEP 2106.04(a)(2). Any limitations not identified above as part of the abstract idea(s) are deemed “additional elements,” and will be discussed in further detail below.
Furthermore, the abstract idea for claims 9 and 17 are identical as the abstract idea for claim 1, because the only difference between claims 1, 9, and 17 is that claim 1 recites a method, whereas claim 9 recites a system and claim 17 recites a non-transitory computer-readable media.
Dependent claims 2-8, 10-13, 15, 16, 18-20 and 22 include other limitations, for example claims
2, 4-6, 10, 12-14, 19 and 20 recite limitations directed to the prediction algorithm and the risk level, but these only serve to further narrow the abstract idea, and a claim may not preempt abstract ideas, even if the judicial exception is narrow, e.g. see MPEP 2106.04. Additionally, any limitations in dependent claims 2-8, 10-13, 15, 16, 18-20 and 22 not addressed above are deemed additional elements to the abstract idea, and will be further addressed below. Hence dependent claims 2-8, 10-13, 15, 16, 18-20 and 22 are nonetheless directed towards fundamentally the same abstract idea as independent claims 1, 9 and 17.
Prong 2 of Step 2A
Claims 1, 9, 17 and 21 are not integrated into a practical application because the additional elements (i.e. any limitations that are not identified as part of the abstract idea) amount to no more than limitations which:
amount to mere instructions to apply an exception – for example, the recitation of the machine-learning model, the structural components of the computer and the user interface, which amounts to merely invoking a computer as a tool to perform the abstract idea, see MPEP 2106.05(f); and/or
generally link the abstract idea to a particular technological environment or field of use – for example, the claim language limiting the data to pet data, which amounts to limiting the abstract idea to the field of healthcare, see MPEP 2106.05(h); and/or
adding insignificant extrasolution activity to the abstract idea, for example mere receiving and displaying data, selecting a particular data source or type of data to be manipulated, and/or insignificant application (e.g. see MPEP 2106.05(g)).
Additionally, dependent claims 2-8, 10-13, 15, 16, 18-20 and 22 include other limitations, but these limitations also amount to no more than mere instructions to apply the exception (e.g. the use of the trained machine-learning model of claim 22), and/or amount to no more than generally linking the abstract idea to a particular technological environment or field of use (e.g. the types of data disclosed in dependent claims 2-3, 5, 9-10, 12, 16-17 and 22), and/or do not include any additional elements beyond those already recited in independent claims 1, 9 and 17, and hence also do not integrate the aforementioned abstract idea into a practical application.
Step 2B
Claims 2-8, 10-13, 15, 16, 18-20 and 22 do not include additional elements that are sufficient to amount to “significantly more” than the judicial exception because the additional elements (i.e. the non-underlined limitations above – in this case, the structural computer components, reception of data and display of data), as stated above, are directed towards no more than limitations that amount to mere instructions to apply the exception, generally link the abstract idea to a particular technological environment or field of use, and/or add insignificant extra-solution activity to the abstract idea, wherein the insignificant extra-solution activity comprises limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrated by:
The Specification expressly disclosing that the additional elements are well-understood, routine, and conventional in nature:
paragraphs 22, 40 and 64 of the Specification discloses that the additional elements (i.e. the structural components of the computer) comprise a plurality of different types of generic computing systems that are configured to perform generic computer functions (i.e. receive and process data) that are well-understood, routine, and conventional activities previously known to the pertinent industry (i.e. healthcare);
Relevant court decisions: The following are examples of court decisions demonstrating well-understood, routine and conventional activities, e.g. see MPEP 2106.05(d)(II):
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added));
ii. Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) ("The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims.");
iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log); and
iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.
Dependent claims 2-8, 10-13, 15, 16, 18-20 and 22 include other limitations, but none of these limitations are deemed significantly more than the abstract idea because, as stated above, the aforementioned dependent claims do not recite any additional elements not already recited in independent claims 1, 9 and 17, and/or the additional elements recited in the aforementioned dependent claims similarly amount to no more than mere instructions to apply the exception (e.g. the use of the trained machine-learning model of claim 22), and/or amount to generally linking the abstract idea to a particular technological environment or field of use (e.g. the types of data disclosed in dependent claims 2-8, 10-13, 15, 16, 18-20 and 22), and hence do not amount to “significantly more” than the abstract idea.
Thus, taken alone, the additional elements do not amount to significantly more than the abstract idea identified above. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, and there is no indication that the combination of elements improves the functioning of a computer or improves any other technology, and their collective functions merely provide conventional computer implementation.
Therefore, whether taken individually or as an ordered combination, claims 1-13 and 15-22 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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 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 of this title, 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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 1-13 and 15-22 are rejected under 35 U.S.C. 103 as being obvious over Holcombe (U.S. PG-Pub 2022/0005607 A1), hereinafter Holcombe, in view of Aktan, Ali Murat, et al. "An evaluation of factors associated with persistent primary teeth." The European Journal of Orthodontics 34.2 (2012): 208-212, hereinafter Factors, further in view of Menavsky et al. (U.S. PG-Pub 2021/0134440 A1), hereinafter Helaoui.
As per claims 1, 9, 17 and 21, Holcombe discloses a method, a non-transitory computer-readable medium storing instructions that, when executed by at least one processor and a computer system for predicting a risk level for the presence of … periodontal disease for one or more pets (Holcombe, see paragraphs 101-121.), the computer system comprising:
at least one memory storing instructions; and at least one processor configured to execute the instructions to perform operations (Holcombe, see paragraphs 101-121.) comprising:
receiving pet … data corresponding to a unique pet identifier from a user device and a pet information database, the pet … data including one or more pet attributes, wherein the one or more pet attributes include one or more biomarkers corresponding to a … genetic predisposition of a pet corresponding to the unique pet identifier (Holcombe, system receives pet data such as characteristics including breed, head shape, size category, weight, body condition and/or age, see paragraphs 12-19 and 108-114, and claim 1. Input data can include genetic biomarkers, see paragraphs 36, 72, 135, 136 and 140. Holcombe discloses use of a unique pet identifier and a database at paragraph 182.);
inputting, by the one or more processors, the one or more pet attributes into a … model that is configured to output a result value indicating a … periodontal disease probability weight for each of the one or more pet attributes (Holcombe, wherein the characteristic is compared with a dataset comprising an occurrence of the periodontal disease in other animals having similar characteristics, in order to arrive at a score, or weight for the particular characteristic/attribute, see paragraphs 20, 27, 28, 30-32, 37, 43, 44, 47-49, and claim 1. System provides various probabilities for various factors input for a given dog based on similar pets, as shown from Figs. 2-9.);
utilizing, by the one or more processors, a … periodontal disease risk level prediction algorithm to select one or more similar pet datasets based on the one or more pet attributes including the one or more … biomarkers, wherein each of the one or more similar pet datasets includes a corresponding … risk level (Holcombe, wherein the scores for multiple characteristics are utilized to determine similar pet datasets (See Figs. 2-9.) in an algorithm to determine the animal’s risk of disease, see paragraphs 55-71 and 124, and claim 1.);
inputting, by the one or more processors, the result value for each of the one or more pet attributes and the result value for each of the one or more similar pet datasets into a logistic regression … model that is configured to determine and output a … risk level (Holcombe, wherein the scores for multiple characteristics are utilized to determine similar pet datasets (See Figs. 2-9.) in an algorithm to determine the animal’s risk of disease, see paragraphs 55-71 and 124, and claim 1. Holcombe discloses use of logistic regression models at paragraphs 134, 139, 141, 142, 198, 212 and 223.);
receiving, by the one or more processors, pet data associated with the pet from one or more pet information databases, wherein the pet data includes a pet veterinarian interaction frequency (Pet data is received from electronic medical records, see paragraphs 11, 181 and 190-192. It is old and well known in the healthcare arts to include visits to a veterinarian in pet medical records, therefore interaction frequency is inherent to pet medical records.);
transmitting, by the one or more processors, the … risk level and the pet data to an analytics module configured to analyze the … risk level and the pet data to determine an analysis statement for a user type, wherein the user type includes a pet owner or a veterinarian (System determines risk level using pet data and outputs an analysis statement such as a determined recommendation, see paragraphs 118, 161, 165 and claim 1. It is old and well known to output veterinarian data for a veterinarian, the Office notes that there is no claimed difference in a statement issued for a pet owner or for a user type, therefore the claim language wherein the user type includes a pet owner or a veterinarian amounts to a nonfunctional description.);
determining, by the one or more processors, one or more recommendations based on the … risk level, wherein the one or more recommendations include identifying … an intervention (Recommendation based on risk is displayed on the graphical user interface, see paragraphs 118, 161, 165 and claim 1.); and
displaying the … periodontal disease risk level, the analysis statement, and the one or more recommendations on one or more user interfaces of the user device (Risk is displayed on the graphical user interface, see paragraphs 118, 161, 165 and claim 1.).
As seen from the title, Holcombe is directed to diagnosing periodontal disease. Holcombe fails to explicitly disclose:
pet image data;
risk and analysis related to persistent deciduous teeth (PDT),
a trained machine-learning model,
use of a second machine-learning model, or
a recommendation of at least one tooth for removal.
Factors teaches that it was old and well known in the art of healthcare communications before the effective filing date of the claimed invention to disclose risk and analysis related to persistent deciduous teeth (PDT) through use of pet image data (Factors, Summary and Introduction, page 208.).
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare communications before the effective filing date of the claimed invention to modify the method of diagnosing oral diseases in animals of Holcombe to include risk and analysis related to persistent deciduous teeth (PDT) through use of pet image data, as taught by Factors, in order to provide an oral diagnostic system that considers more potential oral problems.
Neither Holcombe nor Factors discloses use of a trained machine-learning model, use of a second machine-learning model or a recommendation of at least one tooth for removal.
Menavsky teaches that it was old and well known in the art of healthcare communications before the effective filing date of the claimed invention to disclose use of a trained machine-learning model, use of a second machine-learning model and recommendation of at least one tooth for removal (Menavsky discloses plural uses of trained machine learning models and also a tooth removal recommendation, see paragraphs 3, 7, 19, 27, 42, 48 and Figs. 2, 6 and 7I.) in order to anticipate needed dental care for a patient.
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare communications before the effective filing date of the claimed invention to modify the method of diagnosing oral diseases in animals of Holcombe/Factors to include use of a trained machine-learning model, use of a second machine-learning model and recommendation of at least one tooth for removal, as taught by Menavsky, in order to provide an oral diagnostic system that can anticipate needed dental care for a patient.
Holcombe, Factors and Menavsky are all directed to the processing of patient healthcare data in order to determine risks of various illnesses. Moreover, merely adding a well-known element into a well-known system, to produce a predictable result to one of ordinary skill in the art, does not render the invention patentably distinct over such combination (see MPEP 2141).
A recitation directed to the manner in which a claimed apparatus is intended to be used does not distinguish the claimed apparatus from the prior art, if the prior art has the capability to so perform, see MPEP 2114 (II) and Ex parte Masham, 2 USPQ2d 1647 (Bd. Pat. App. & Inter. 1987). “Language that suggest or makes optional but does not require steps to be performed or does not limit a claim to a particular structure does not limit the scope of a claim or claim limitation”, see MPEP 2111.04.
The following limitation is interpreted as an intended use of the claimed invention:
21. … in order to decrease the risk of periodontal disease that could be a consequence of PDT.
The prior art is capable of performing the intended use recitation, therefore the prior art meets the limitations.
As per claims 2-8, 10-13, 15, 16, 18-20 and 22, Holcombe/Factors/Menavsky discloses claims 1, 9 and 17, detailed above. Holcombe/Factors/Menavsky also discloses:
2,10,20. the analyzing, by the one or more processors, the result value to determine the PDT risk level further comprising:
utilizing, by the one or more processors, the PDT risk level prediction algorithm to determine the PDT risk level by comparing the result value corresponding to each of the one or more pet attributes with the one or more similar pet datasets (Holcombe, wherein the scores for multiple characteristics are utilized in an algorithm to determine the animal’s risk of disease, see paragraphs 55-71 and 124, and claim 1.);
3,11,18. wherein the pet data includes at least one of: a medical record corresponding to the pet, pet data input via the user device, or pet data stored in one or more pet data stores (Holcombe, paragraphs 107-108.);
4,12,19. wherein the PDT risk level includes a low risk, a medium risk, or a high risk (Holcombe, paragraphs 26 and 65.);
5,13. wherein the PDT risk level indicates a probability of the pet being diagnosed with PDT (Risk is displayed on the graphical user interface, see paragraphs 118, 161, 165 and claim 1);
6. determining, by the one or more processors, one or more statements corresponding to an oral health level of the pet (Holcombe, see Abstract and paragraphs 22-25, 82-88 and 164, and claim 1.); and
displaying, by the one or more processors, a health report that includes the one or more statements on the one or more user interfaces of the user device (Holcombe, see Abstract and paragraphs 22-25, 82-88 and 164, and claim 1.);
7,15. wherein the one or more pet attributes include one or more of: a pet type including a breed, a pet head shape, a pet weight size category, a pet weight condition, a pet body condition, a predicted pet size category, a pet adult weight category, a pet age, a pet medical interaction frequency, a pet plan, or a last medical interaction (Holcombe, system receives pet data such as characteristics including breed, head shape, size category, weight, body condition and/or age, see paragraphs 12-19 and 108-114, and claim 1.); and
8,16. wherein the pet weight size category includes at least one of: an extra-small category, a small category, a medium-small category, a medium-large category, a large category, or an extra-large category (Holcombe, paragraph 37.);
22. wherein training the machine-learning model includes analyzing, by the one or more processors, via the machine-learning model, one or more training result values of one or more attributes, one or more training datasets, and one or more training PDT risk levels to determine one or more associations (Holcombe discloses training a model by analyzing attributes from training datasets comprising risk levels to make associations, see paragraphs 104, 133, 165 and claim 14. As shown above, Helaoui discloses the machine-learning model, see paragraphs 12, 15, 30, 31, 72, 73, 87-93 and 152.).
Response to Arguments
Applicant’s arguments filed 25 February 2026 concerning the rejection of all claims under 35 U.S.C. 101 and 103(a) have been fully considered but they are not persuasive.
With regard to the rejection of the claims under 35 USC 101, Applicant argues on pages 13-19 that the claims comprise statutory material because:
A. They recite elements that are not “Methods of Organizing Human Activity” and also recite additional elements that illustrate integration into a practical application because “the amended claimed features improve the efficiency and accuracy of the technical field of detecting and mitigating PDT.”
B. Additional elements integrate the abstract idea into a practical application because they recite methods of diagnosing and recommending oral treatment.
The Office respectfully disagrees. Please see the statutory rejection of the claims, issued above, wherein the claims, including the amended elements, are shown to be directed to an abstract idea, without significantly more.
MPEP 2106. 04(a)(2)(II) states that a claimed invention is directed to certain methods of organizing human activity if the identified claim elements contain limitations that encompass fundamental economic principles or practices, commercial or legal interactions, or managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions. The Examiner submits that the identified claim elements represent a series of rules or instructions that a person or persons, with or without the aid of a computer, would follow to diagnose an oral disorder risk. Furthermore, the Examiner submits that healthcare itself is inherently represents the organization of human activity. Applicant has not pointed to anything in the claims that fall outside of this characterization. Because the claim elements fall under a series of rules or instructions that a person or persons would follow to [summarize the invention], the claimed invention is directed to an abstract idea.
Further, MPEP 2106.04(d)(1) states that a practical application may be present where the claimed invention improves another technology. See also MPEP 2106.05(a)(II). Applicant’s claim is confined to a general-purpose computer and does not recite “another technology.” Because no other technology is recited in the claim, the claim cannot improve another technology (see, e.g., MPEP 2106.05(I)(A)(i) describing an example of an improvement to another technology where the abstract idea implemented on a computer improved the claimed additional element of a rubber molding machine).
Regarding B., MPEP 2106.04(d)(1) and MPEP 2106.05(a) indicates that a practical application may be present where the claimed invention provides a technical solution to a technical problem. See, e.g., DDR Holdings, LLC. v. Hotels.com, L.P., 773 F.3d 1245, 1259 (Fed. Cir. 2014) (finding that claiming a website that retained the “look and feel” of a host webpage provided a technological solution to the problem of retention of website visitors by utilizing a website descriptor that emulated the “look and feel” of the host webpage, where the problem arose out of the internet and was thus a technical problem). Here, the Applicant’s argued problem is not a technological problem caused by the computing environment. The problem of diagnosing and recommending oral treatment was not a problem cause by the computer, is it a problem that existed and/or exists regardless of whether a computer is involved in the process. At best, Applicant’s identified problem is a healthcare problem. Because no technological problem is present, the claims do not provide a practical application.
With regard to the rejection of the claims under 35 USC 103, Applicant argues on pages 19-21 that the previously cited references fail to disclose the claims as amended.
Applicant's arguments have been fully considered but are moot in view of the new ground(s) of rejection, specifically with reference to the new reference necessitated by amendment, Menavsky, as detailed above, or because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references.
In conclusion, all of the limitations which Applicant disputes as missing in the applied references, including the features newly added by amendment, have been fully addressed by the Office as either being fully disclosed or obvious in view of the collective teachings of Holcombe, Factors, Menavsky and Helaoui, based on the logic and sound scientific reasoning of one ordinarily skilled in the art at the time of the invention, as detailed in the remarks and explanations given in the preceding sections of the present Office Action and in the prior Office Actions (28 November 2025, 27 June 2025 and 18 March 2025), and incorporated herein.
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 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 date of this final action.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to Mark Holcomb, whose telephone number is 571.270.1382. The Examiner can normally be reached on Monday-Friday (8-5). If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, Kambiz Abdi, can be reached at 571.272.6702.
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/MARK HOLCOMB/
Primary Examiner, Art Unit 3685
17 March 2026