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 .
Response to Amendment
The following Office action in response to communications received June 2, 2026. Claims 1, 3, 11, 13, 21, 23-25 and 27-28 have been amended. Therefore, claims 1, 3, 11, 13, 21, 23-25, and 27-33 are pending and addressed below.
Applicants’ amendments to the claims are not sufficient to overcome the 35 USC § 101 rejections set forth in the previous office action dated February 26, 2026.
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, 3, 11, 13, 21, 23–25, and 27–33 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. Based upon consideration of all the relevant factors with respect to the claims, the claims are directed to non-statutory subject matter which do not include additional elements that are sufficient to amount to significantly more than the judicial exception because of the following analysis:
Independent claims 1, 11, and 29 are directed to the abstract idea of evaluating patient medical information to predict the presence of an implant or foreign object, assigning a safety categorization, and providing the resulting information for use in a radiology workflow.
Independent claims 1, 11, and 29 recite, in substance:
Receiving medical imaging information and textual medical-record information about a patient; analyzing the information to predict whether an implant or foreign object is present; categorizing the object according to conditions for safe scanning; and providing the prediction or information related to magnetic exposure to a radiology management system.
The limitations of claims 1, 3, 11, 13, 21, 23–25, and 27–33, under their broadest reasonable interpretation, cover the performance of:
Mental processes, including observing medical images and medical records, evaluating whether an implant or foreign object is present, determining conditions for safe scanning, and communicating the resulting evaluation.
Mathematical concepts, including generating a likelihood score, comparing the score with a threshold, generating labeled training data, adjusting model weights to minimize error, and retraining a model based on validation information.
Certain methods of organizing human activity, including managing a clinical screening workflow by providing patient safety determination to a radiology management system and updating the system with validation information.
But for the recitation of generic computer components and generic AI/ML and NLP functionality, the claim steps are simply reviewing patient imaging and medical records, determining whether a patient has an implant or foreign object, determining conditions under which the patient may safely be scanned, communicating that determination, and maintaining the determination for future clinical screening.
The claims recite additional elements such as:
One or more processors.
One or more memories storing processor-executable instructions.
An AI module, an AI engine, and an NLP engine.
A trained AI module and labeled training data.
A radiology management system.
A likelihood score, confidence level, probability, and threshold.
Validation information and record updating.
Non-transitory computer-readable media.
These elements are recited at a high level of generality and merely use generic computer components to receive data, analyze data, generate a prediction or score, compare the score to a threshold, store information, update a record, and communicate information to a radiology management system.
The claims do not recite a particular AI-model architecture, image-analysis process, NLP process, image-feature extraction technique, model-training algorithm, loss function, weight-adjustment mechanism, validation methodology, model-retraining technique, or manner of combining imaging information with textual medical records. The claims instead recite the desired results of determining presence or absence of an implant or foreign object and providing an associated safety categorization.
The additional elements do not integrate the abstract idea into a practical application. The claims apply the identified abstract ideas using generic computer components in the medical/radiology field.
The recitation of analyzing “medical imaging information” and “textual medical records information” does not provide a technological improvement because the claims do not specify how the image data or text is processed. The recitation of an “AI engine” and “NLP engine” merely invokes generic tools to perform the claimed evaluation.
The recitation of a “categorization … indicative of one or more conditions under which the implant or the foreign object can safely be scanned” is a safety conclusion resulting from the abstract evaluation. The claims do not require control of MRI equipment, alteration of scanner operation, modification of magnetic-field strength, modification of radio-frequency output, modification of scan parameters, or another technical action based on the categorization.
Similarly, the recitations of generating a labeled dataset, adjusting weights “to minimize error,” retraining based on validation information, and providing a likelihood score or probability are stated only at a result-oriented level. The claims do not recite a particular technological mechanism for implementing those functions or an improvement to model, computer, image-processing, or NLP operation.
Providing a prediction to a radiology management system and updating that system with validation information are generic communication and data-storage functions. The recitation that future use of information does not require additional analysis merely reflects storing a prior determination for later retrieval; the claims do not recite a particular data structure, cache technique, or database improvement.
Accordingly, the claims do not improve the functioning of a computer, network, AI/ML model, NLP model, image-processing system, or radiology management system. They merely apply the abstract idea in a generic computing environment and limit its use to the field of magnetic-exposure screening.
The ordered combination of claim elements adds nothing significantly more than the abstract idea itself. The use of generic processors, memory, computer-readable media, AI/ML and NLP engines, data storage, scoring, thresholding, radiology management systems, and user validation is conventional and routine.
The claims recite generic components performing their ordinary functions of receiving information, analyzing information, generating a result, storing information, and communicating a result. The claims do not recite an unconventional arrangement or a nonconventional technological mechanism that transforms the abstract idea into patent-eligible subject matter.
Any storage, updating, displaying, transmitting, reporting, or providing of the prediction or validation information is insignificant extra-solution activity.
Accordingly, claims 1, 3, 11, 13, 21, 23–25, and 27–33 are directed to an abstract idea without significantly more and therefore are not patent eligible under 35 U.S.C. §101.
Subject Matter Free of Prior Art
Examiner notates below the reasons why the claims overcome the prior art. The limitations are most likely to distinguish over the cited combination of Patent No.: US 11756681 B2 to Katra et al. in view of Patent No.: US 12154689 B2 to Jameel. are:
generating, by the AI module analyzing the received medical information, a prediction that includes (i) a presence of an implant or a foreign object in a body of the patient;
a categorization, of the implant or the foreign object, that is indicative of one or more conditions under which the implant or the foreign object can safely be scanned;
wherein the generating includes analyzing, by the AI engine, the medical imaging information and analyzing, by the NLP engine, the textual medical records information;
providing, the prediction generated by the AI module to a radiology management system; and
the categorization is an MR Conditional categorization.
Response to Arguments
Applicant's arguments, filed on June 2, 2026, with respect to argument in the remarks, have been considered but are moot in view of the new ground(s) of rejection necessitated by the new limitations added to Claims 1, 3, 11, 13, 21, 23-25 and 27-28.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Pat. No.: US 12260555 B2; Techniques for remote monitoring of a patient and corresponding medical device(s) are described. The remote monitoring comprises identifying a first set of images that represent a particular location of a body of a patient in which at least one component of an implantable medical device (IMD) coincides, determining a projection of alteration characteristics of the particular location of the body, identifying a second set of images, determining a second set of alteration characteristics, comparing the second set of alteration characteristics to the projection, and identifying a potential abnormality at the particular location of the body.
Pat. No.: CA 3225227 A1; A computer-implemented method for processing at least one image of a location of a body of a subject. The method may comprise obtaining the at least one image, and using a trained algorithm to classify the at least one image or a derivative thereof to a category among a plurality of categories comprising a first category and a second category. The classifying may comprise applying a image processing algorithm. The method may comprise, based at least in part on the classifying, designating the at least one image or derivative thereof as having a first or second priority (e.g., lower priority or urgency than the first priority) for radiological assessment if the at least one image is classified to the first or second category, respectively. The method may comprise generating an electronic assessment of the subject, such as a negative report indicative of the subject not having a health condition.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to EDWARD B WINSTON III whose telephone number is (571)270-7780. The examiner can normally be reached M-F 1030 to 1830.
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/EDWARD B WINSTON III/ Examiner, Art Unit 3683
/ROBERT W MORGAN/ Supervisory Patent Examiner, Art Unit 3683
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