DETAILED ACTION
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This Office action is in response to Applicant’s communication filed on September 2, 2025. Amendments to claims 1, 5 and 6, cancellation of claims 2, 7-8, 11 and 12 and addition of new claims 15-20 have been entered. Claims 1, 5, 6, and 15-20 are pending and have been examined. The statement of reasons for the indication of allowable subject matter (over prior art) was already discussed in the Office Action mailed on November 3, 2023 and hence not repeated here. The rejections and response to arguments are stated below.
Claim Rejections - 35 USC § 101
2. 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.
3. Claims 1, 5-6, and 15-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
The claims recite a computer-implemented method for point of care evaluation of a proposed treatment plan relating to oral care (in the context of processing insurance claims), which is considered a judicial exception because it falls under the category of “Certain Methods of organizing human activity” such as resolving/fulfilling agreements as discussed below. This judicial exception is not integrated into a practical application as discussed below. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception as discussed below.
Analysis
Step 1: In the instant case, exemplary claim 1 is directed to a method.
Step 2A – Prong One: The limitations of “A computer-implemented method for point of care evaluation of a proposed treatment plan relating to oral care delivered to a subject patient during a visit of the patient to a dental clinic (in the context of processing insurance claims), the
the proposed treatment plan comprising an oral care procedure, the method
using at least one processor to perform, during the visit of the patient to the dental clinic, acts of:
receiving (i) dental image data, pertaining to the subject patient, obtained from a diagnostic imaging system located in a dental clinic, the dental image data comprising a radiograph, and (ii) patient data maintained for the subject patient;
processing the dental image data, including the radiograph, and at least some of the patient data, using a set of machine learning models to generate diagnostic data characterizing the dental image data, wherein the set of machine learning models includes an image classification neural network model and a prediction model trained to detect clinical conditions from the dental image data, the processing comprising:
classifying the radiograph, using an image classification neural network model, into an image class in a set of image classes comprising a bitewing radiograph, a periapical radiograph, an occlusal radiograph, and a panoramic radiograph;
performing, based on results of the classifying, one or more of:
automated image segmentation processing to determine outlines of one or more teeth visible in the radiograph;
automated tooth number processing to associate standardized identifiers with the one more teeth visible in the radiograph; and/or
automated key point detection processing to identify tips of roots of the one or more teeth visible in the radiograph;
detecting one or more clinical conditions from the dental image data using the prediction model, the one or more clinical conditions including caries and presence of one or more crowns, the detecting comprising using the prediction model to detect caries in the one more teeth visible in the radiograph and/or detecting presence of one or more crowns on one or more teeth visible in the radiograph;
generating an evaluation of the proposed treatment plan, including the oral care procedure, by determining efficacy of the proposed treatment plan based on the diagnostic data; and
communicating the evaluation of the proposed treatment plan in real time to an endpoint located in the dental clinic,
wherein the evaluation indicates approval of the proposed treatment plan, and the
method further comprises performing the oral care procedure, part of the proposed treatment plan, during the visit of the patient to the dental clinic” as drafted, when considered collectively as an ordered combination without the italicized portions, is a process that, under the broadest reasonable interpretation, covers the category of “Certain Methods of organizing human activity” such as resolving/fulfilling agreements.
“A computer-implemented method for point of care evaluation of a proposed treatment plan relating to oral care delivered to a subject patient during a visit of the patient to a dental clinic (in the context of processing insurance claims)” is a fundamental economic practice such as processing insurance claims. Claims are not interpreted in a vacuum. Claims are interpreted in light of the Specification. The title of the invention (Point of care claim processing system and method), and the description in at least paragraphs [0002] – [0004], [0008], and [0025] makes it clear that the claims are directed to computer processes, for point of care processing (of an insurance claim) relating to oral care delivered to a subject patient during a visit of the patient to a dental clinic. Hence, the claims recite a fundamental economic practice such as resolving/ fulfilling agreements.
Generating an evaluation of the proposed treatment plan including the oral care procedure, by determining efficacy of the proposed treatment plan based on the diagnostic data; and communicating the evaluation of the proposed treatment plan in real time to an endpoint located in the dental clinic, wherein the evaluation indicates approval of the proposed treatment plan (in the context of processing an insurance claim), the method further comprises performing the oral care procedure, part of the proposed treatment plan, during the visit of the patient to the dental clinic, is a form of legal interaction including fulfilling agreements (in the insurance contract) among the parties concerned. Hence, the steps of the claim, considered collectively as an ordered combination without the italicized portions, covers the abstract category of “Certain Methods of organizing human activity”.
That is, in claim 1, other than, at least one processor, a diagnostic imaging system, a set of machine learning models including an image classification neural network model and a prediction model, and automated processing including automated image segmentation processing, automated tooth number processing, and automated key point detection processing, nothing in the claim precludes the steps from being performed as a method of organizing human activity. If the claim limitations, under the broadest reasonable interpretation, covers methods of organizing human activity but for the recitation of generic computer components, then it falls within the “Certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A – Prong Two: The judicial exception is not integrated into a practical application. In particular, claim 1 only recites the additional elements of at least one processor, a diagnostic imaging system, a set of machine learning models including an image classification neural network model and a prediction model, and automated processing including automated image segmentation processing, automated tooth number processing, and automated key point detection processing to perform all the steps. A plain reading of Figures 1-5 and associated descriptions in at least paragraphs [0016], and [0027] – [0036] reveals that the at least one processor may be one generic processor or more than one generic (single- or multi-processor) computer suitably programmed to execute the claimed steps. The diagnostic imaging system, the set of machine learning models including an image classification neural network model and a prediction model, are broadly interpreted to include generic computer components suitably programmed to perform the corresponding functions. The automated processing including automated image segmentation processing, automated tooth number processing, and automated key point detection processing are similarly broadly interpreted to include generic computer software/process suitably programmed to perform the corresponding functions. Hence, the additional elements in the claims are all generic components suitably programmed to perform their respective functions. The additional elements in all the steps are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions) such that it amounts no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Hence, claim 1 is directed to an abstract idea.
Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, using the additional elements (identified above) to perform the claimed steps amounts to no more than mere instructions to apply the exception using a generic computer component. The additional elements of the instant underlying process, when taken in combination, together do not offer substantially more than the sum of the functions of the elements when each is taken alone. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Hence, independent claim 1 is not patent eligible.
Dependent claims 5-6, and 15-20, when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations only refine the abstract idea further.
For instance, in claims 5-6, the steps “wherein the receiving the patient data includes receiving information selected from the group consisting of (a) patient demographics, (b) subscriber demographics for the patient, (c) a proposed treatment plan for the patient, (d) periochart data, (e) previously completed treatments, (f) patient health history, and (g) patient medication list” and “wherein the patient demographics are selected from the group consisting of patient name, patient date of birth, patient id number, and patient relationship to a subscriber” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the data used in the intermediate steps of the underlying process. Specification [0027] makes it clear that subscriber demographics for the patient includes information identifying a subscriber to an insurance plan potentially applicable to the patient.
In claims 15-17 the steps “wherein classifying the radiograph comprises performing automated image segmentation processing to determine outlines of one or more teeth visible in the radiograph”,
“wherein classifying the radiograph comprises performing automated tooth number processing to associate standardized identifiers with the one more teeth visible in the radiograph”,
“wherein classifying the radiograph comprises performing automated Key point detection processing to identify tips of roots of the one or more teeth visible in the radiograph” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the classification process used in the intermediate steps of the underlying process, using suitably programmed generic computer components.
In claims 18-20 the steps “wherein the neural network model comprises a convolutional neural network comprising one or more convolutional layers”,
“wherein the neural network model has a transformer architecture including an attention mechanism to weight network connections according to their significance”, and
“wherein the neural network model comprises an encoder, trained as part of an encoder, and a classification head coupled to an output of the encoder” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the neural network model used in the intermediate steps of the underlying process.
In all the dependent claims, the judicial exception is not integrated into a practical application because the limitations are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using generic computer components. Also, the claims do not affect an improvement to another technology or technical field; the claims do not amount to an improvement to the functioning of a computer system itself; the claims do not affect a transformation or reduction of a particular article to a different state or thing; and the claims do not move beyond a general link of the use of an abstract idea to a particular technological environment. In addition, the dependent claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements of the instant underlying process, when taken in combination, together do not offer substantially more than the sum of the functions of the elements when each is taken alone. The claims as a whole, do not amount to significantly more than the abstract idea itself. For these reasons, the dependent claims also are not patent eligible.
Response to Arguments
4. In response to Applicants arguments on pages 5-7 of the Applicant’s remarks that the claims are patent-eligible under 35 USC 101 when considered under MPEP 2106, the Examiner respectfully disagrees.
Response to Applicants’ arguments in Section A of the remarks:
The claims recite a computer-implemented method for point of care evaluation of a proposed treatment plan relating to oral care delivered to a subject patient during a visit of the patient to a dental clinic (in the context of processing an insurance claim), which is considered a judicial exception because it falls under the category of “Certain Methods of organizing human activity” such as fundamental economic practice as well as commercial legal interactions including agreements (in the insurance contracts). Claims are not interpreted in a vacuum. While limitations are not imported from the Specification to the claims, the claims are interpreted in light of the Specification. The title of the invention (Point of care claim processing system and method), and the description in at least paragraphs [0002] – [0004], [0008], and [0025] makes it clear that the claims are directed to computer processes, for point of care processing of an insurance claim relating to oral care delivered to a subject patient during a visit of the patient to a dental clinic. Hence, the claims recite a fundamental economic practice such as processing insurance claims.
Generating an evaluation of the proposed treatment plan including the oral care procedure, by determining efficacy of the proposed treatment plan based on the diagnostic data; and communicating the evaluation of the proposed treatment plan in real time to an endpoint located in the dental clinic, wherein the evaluation indicates approval of the proposed treatment plan (in the context of processing an insurance claim) and the method further comprises performing the oral care procedure, part of the proposed treatment plan, during the visit of the patient to the dental clinic is a form of legal interaction including resolving/fulfilling agreements (in the insurance contract) among the parties concerned. Hence, the steps of the claim, considered collectively as an ordered combination without the italicized portions, covers the abstract category of “Certain Methods of organizing human activity”.
Generating an evaluation of the proposed treatment plan by determining, by a decision support system, efficacy of the proposed treatment plan based on the diagnostic data; and communicating the evaluation of the proposed treatment plan in real time (in the context of processing an insurance claim) and further comprising performing the oral care procedure, part of the proposed treatment plan, during the visit of the patient to the dental clinic is a form of legal interaction including resolving/fulfilling agreements in the insurance contract among the parties concerned. The steps of the claim considered collectively as an ordered combination is similar to the abstract concept of generating rule‐based tasks for processing an insurance claim (See Accenture Global Services, GmbH v. Guidewire Software) (Citations omitted) and the abstract concept of managing an insurance policy (See Bancorp Services v. Sunlife). Hence, the steps of the claim, considered collectively as an ordered combination, covers the abstract category of “Certain Methods of organizing human activity”. The additional elements of a computer system, a set of suitably programmed machine learning models (including an image classification model and a prediction model) and a decision support system are used to apply the abstract idea of point of care processing of an insurance claim.
The claimed steps (in exemplary claim 1), are similar to generating rule‐based tasks for processing an insurance claim (See Accenture Global Services, GmbH v. Guidewire Software) (Citations omitted) and managing an insurance policy (See Bancorp Services v. Sunlife). The additional elements (identified in the rejection) are used as tools in their ordinary capacity, to apply the abstract concept. The fact that these concepts are applied to the dental field does not change the underlying nature of the abstract idea of processing of an insurance claim. Therefore, the Applicant’s arguments are not persuasive.
Response to Applicants’ arguments in Section B of the remarks:
According to MPEP 2106, limitations that are indicative of integration into a practical application include:
Improvements to the functioning of a computer, or to any other technology or technical field - see MPEP 2106.05(a)
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition
Applying the judicial exception with, or by use of, a particular machine - see MPEP 2106.05(b)
Effecting a transformation or reduction of a particular article to a different state or thing - see MPEP 2106.05(c)
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception - see MPEP 2106.05(e).
In the instant case, the judicial exception is not integrated into a practical application, because none of the above criteria is met. The additional elements in the claims are at least one processor, a diagnostic imaging system, a set of machine learning models including an image classification neural network model and a prediction model, and automated processing including automated image segmentation processing, automated tooth number processing, and automated key point detection processing to perform all the steps. A plain reading of Figures 1-5 and associated descriptions in at least paragraphs [0016], and [0027] – [0036] reveals that the at least one processor may be one generic processor or more than one generic (single- or multi-processor) computer suitably programmed to execute the claimed steps. The diagnostic imaging system, the set of machine learning models including an image classification neural network model and a prediction model, are broadly interpreted to include generic computer components suitably programmed to perform the corresponding functions. The automated processing including automated image segmentation processing, automated tooth number processing, and automated key point detection processing are similarly broadly interpreted to include generic computer software/process suitably programmed to perform the corresponding functions. Hence, the additional elements in the claims are all generic components suitably programmed to perform their respective functions. The additional elements in all the steps are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions) such that it amounts no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The additional elements in the claims (identified in the rejection) are used in their normal capacity to apply the abstract idea of a method for point of care processing of an insurance claim relating to oral care delivered to a subject patient during a visit of the patient to a dental clinic. Hence, the claims are directed to an abstract idea. The fact that these concepts are applied to the dental field does not change the underlying nature of the abstract idea of processing of an insurance claim. “Performing an oral care procedure on a patient” is a part of fulfilling agreements between the parties to the insurance contract. It does not involve any improvements to another technology, technical field, or improvements to the functioning of the computer itself. Hence, the claims are directed to an abstract idea. Therefore, the Applicants’ arguments are not persuasive.
For these reasons and those discussed in the rejection, the rejections under 35 USC § 101 are maintained.
Conclusion
5. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
(a) Tabak; Joshua Alexander et al. (US Pub. 2024/02742 A1) discloses systems and methods for utilizing machine learning techniques to analyze data associated with one or more dental practices to identify missed treatment opportunities, future treatment opportunities, or provider performance metrics. The treatment opportunities or performance metrics may be determined or identified based at least in part on a comparison of patient data, such as data stored in association with a dental office's practice management system, with the output of one or more machine learning models' processing of associated radiograph images of the dental office's patients. The one or more machine learning models may include models that identify, from image data of a radiograph, a dental condition depicted in the radiograph, which may be mapped by a computer system to a corresponding dental treatment recommended for the identified dental condition.
6. Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Narayanswamy Subramanian whose telephone number is (571) 272-6751. The examiner can normally be reached Monday-Friday from 9:00 AM to 5:00 PM. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Abhishek Vyas can be reached at (571) 270-1836. The fax number for Formal or Official faxes and Draft to the Patent Office is (571) 273-8300.
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/Narayanswamy Subramanian/
Primary Examiner
Art Unit 3691
October 9, 2025