DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This communication is in response to the amendment received on 11/06/2025. Claims 17-32 remain pending in this application.
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 17-32 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
Claims 17-24 are drawn to a system which is within the four statutory categories (i.e. machine). Claims 25-30 are drawn to a method which is within the four statutory categories (i.e. process). Claims 31-32 are drawn to a non-transitory medium which is within the four statutory categories (i.e. manufacture).
Step 2A, Prong 1:
Claims 17, 25 and 31 recite “…obtaining, for a plurality of patients of a dental provider, patient records originating from a practice management system of the dental provider; providing, for each of the plurality of patients, at least one radiograph of the patient as input to at least one trained machine learning model of the one or more machine learning models; receiving, for each of the plurality of patients, output of the at least one machine learning model that is provided with the input comprising the at least one radiograph of the patient, wherein the output of the at least one machine learning model identifies at least one dental condition determined to be depicted in the at least one radiograph of the patient; comparing conditions identified in radiographs by the at least one machine learning model with treatments identified in corresponding patient records from the practice management system; based at least in part on instances in which a condition identified by the at least one machine learning model does not match corresponding data from records in the practice management system, identifying a plurality of missed periodontal opportunities associated with the dental provider, wherein the instances are identified based at least in part on the data mapping each of the plurality of dental conditions to a corresponding dental treatment;…” and the limitations of obtaining…patient records…; receiving…output…comprising at least one radiograph of the patient…; comparing conditions…with treatments identified in corresponding patient records form the practice management system; based at least in part on instances in which a condition identified by the at least one machine learning model does not match corresponding data from records in the practice management system, identifying a plurality of missed periodontal opportunities associated with the dental provider…” correspond to “certain methods of organizing human activity”. This is a method of managing interactions between people, such as user following rules and instructions. The mere nominal recitation of a generic computing devices/processor does not take the claims out of the methods of organizing human interactions grouping.
The computing devices and the processor described in the current specification as generic computing devices, such as [0086] of the current specification recites”… A computing environment can include any type of computer system, including, but not limited to, a computer system based on a microprocessor, a mainframe computer, a digital signal processor, a portable computing device, a device controller, or a computational engine within an appliance, to name a few.”.
The limitations of “training, using a plurality of training images depicting dental radiographs as training image data, one or more machine learning models to localize and classify dental conditions depicted in the training image data” and “comparing conditions identified in radiographs by the at least one machine learning model with treatments identified in corresponding patient records from the practice management system” correspond to mathematical relationships, therefore the limitations fall within the “mathematical concept” grouping of abstract ideas.
After considering all claim elements, both individually and in combination and in ordered combination, it has been determined that the claims do not amount to significantly more than the abstract idea itself.
Dependent claims also correspond to “mathematical concepts”, such as claim 19 recites “…the one or more machine learning models utilize deep learning to (1) localize one or more regions in the radiograph which contain features of interest and (2) classify each of the one or more regions as depicting one or more dental pathologies, restorations, anatomies, or anomalies”, and claim 23 recites “…the criteria set by the user comprises doctor-specific weights to be applied by the computer system to each of a plurality of different conditions or indications that the one or more machine learning models are trained to detect in radiographs”, since these limitations are directed to mathematical relationships (mathematical algorithms).
Dependent claims also correspond to “certain methods of organizing human activity”, such as, claim 26 recites “…identifying a first patient with potential unmet dental treatment needs based on a comparison of output of the one or more machine learning models with information from a patient record of the first patient”, and claim 32 recites “…determining a percentage representing how often the dental provider missed periodontal opportunities over a time period based at least in part on the plurality of missed periodontal opportunities”, since these limitations are directed to managing interactions between people, such as user following rules and instructions.
Claims 18, 20-22, 24 and 27-30 are ultimately dependent from claims 17, 25, 31 and include all the limitations of claims 17, 25, 31. Therefore, claims 18, 20-22, 24 and 27-30 recite the same abstract idea. Claims 18, 20-22, 24 and 27-30 describe a further limitation regarding the basis for identifying a plurality of periodontal opportunities associated with the dental provider. These are all just further describing the abstract idea recited in claims 17, 25, 31, without adding significantly more.
Step 2A, Prong 2:
This judicial exception is not integrated into a practical application. In particular, claims recite the additional elements of “one or more electronic data stores that store data mapping…”, “a processor in communication with the one or more electronic data stores and configured with processor-executable instructions to perform…training, using a plurality of training images depicting dental radiographs as training image data, one or more machine learning models to localize and classify dental conditions depicted in the training image data” and using the processor for perform the steps of comparing conditions and identifying missed periodontal opportunities.
These additional elements correspond to hardware and software elements, these limitations are not enough to qualify as “practical application” being recited in the claims along with the abstract idea since these elements are merely invoked as a tool to apply instructions of the abstract idea in a particular technological environment, and mere instructions to apply/implement/automate an abstract idea in a particular technological environment and merely limiting the use of an abstract idea to a particular field or technological environment do not provide practical application for an abstract idea (MPEP 2106.05(f) & (h)).
Claims also recite other additional limitations beyond abstract idea, including functions such as obtaining/receiving data from/to a database, generating/displaying data are insignificant extra-solution activities (see MPEP 2106.05 (g)), which do not provide a practical application for the abstract idea.
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 claims are 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, the additional element of using a processor to perform both the comparing and identifying steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
The claims are not patent eligible.
Response to Arguments
Applicant's arguments filed 11/06/2025 have been fully considered but they are not persuasive. Applicant’s arguments will be addressed below in the order in which they appear.
Argument 1: Claims are not directed to an abstract idea:
Applicant argues that claims are not directed to “certain methods of organizing human activity”, such as user following rules and instructions, since claims recite machine learning model processing of dental radiographs and subsequent automated comparison of the model’s output with patient records from a practice management systema and generating a user interface, but there is no managing of a human, directing a human, interaction received from a human or other recitation of managing of interactions between people.
In response, Examiner submits that the limitations of obtaining data and identifying a plurality of missed opportunities using a genetic computing device, doing generic computing functions correspond to user following rules and instructions, and therefore an abstract idea of “certain methods of organizing human activity”. MPEP recite “…the sub-groupings encompass both activity of a single person (for example, a person following a set of instructions or a person signing a contract online) and activity that involves multiple people (such as a commercial interaction), and thus, certain activity between a person and a computer (for example a method of anonymous loan shopping that a person conducts using a mobile phone) may fall within the "certain methods of organizing human activity" grouping.” in § 2106.04(a)(2)II. In this case, the claim limitations are directed to a certain activity between a person and a computer that the person identifies a plurality of missed periodontal opportunities using a generic computing device, performing generic computing devices of receiving and comparing data.
Applicant argues that the Office Action has not provided any support for its assertion that the claim elements involving “training, using a plurality of training images depicting dental radiographs as training image data, one or more machine learning models to localize and classify dental conditions depicted in the training image data” and “comparing conditions identified in radiographs by the at least one machine learning model with treatments identified in corresponding patient records from the practice management system” allegedly “correspond to mathematical relationships”.
In response, Examiner submits that the current specification describes the machine learning algorithm as “The machine learning architectures used for training may include various forms of neural networks, deep learning models, and/or other architectures for accomplishing classification and/or localization via supervised and/or unsupervised learning.” in [0037], and based on the USPTO’s 2024 Guidance Update on Patent Eligibility, these machine learning algorithms correspond to “mathematical concepts”.
Argument 2: Claims are directed to a practical application:
Applicant argues that claims are directed to practical application, since they recite specific steps performed by a computer system subsequent to obtaining results of the one or more machine learning models to identify missed periodontal opportunities.
In response, Examiner submits that, as indicated in the rejection above, the additional elements of “one or more electronic data stores that store data mapping…”, “a processor in communication with the one or more electronic data stores and configured with processor-executable instructions to perform…training, using a plurality of training images depicting dental radiographs as training image data, one or more machine learning models to localize and classify dental conditions depicted in the training image data” and using the processor for perform the steps of comparing conditions and identifying missed periodontal opportunities correspond to hardware and software elements, these limitations are not enough to qualify as “practical application” being recited in the claims along with the abstract idea since these elements are merely invoked as a tool to apply instructions of the abstract idea in a particular technological environment, and mere instructions to apply/implement/automate an abstract idea in a particular technological environment and merely limiting the use of an abstract idea to a particular field or technological environment do not provide practical application for an abstract idea (MPEP 2106.05(f) & (h)).
Argument 3: Claims are directed to significantly more than the abstract idea:
Applicant argues that the current claims recite significantly more than the abstract idea, since claim 17 recites limitations regarding training and using machine learning models along with subsequent determinations.
In response, Examiner submits that as discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform both the comparing and identifying steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Claim limitations correspond to generally linking the use of the judicial exception to a particular technological environment or field of use (See MPEP § 2106.05).
Therefore, the arguments are not persuasive and claims are rejected under 35 U.S.C. §101 as being directed to non-statutory subject matter.
Conclusion
THIS ACTION IS MADE FINAL. 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DILEK B COBANOGLU whose telephone number is (571)272-8295. The examiner can normally be reached 8:30-5:00 ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Obeid Mamon can be reached at (571) 270-1813. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/DILEK B COBANOGLU/Primary Examiner, Art Unit 3687