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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 10/07/2024 and 01/30/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Drawings
The drawings filed on 10/07/2024 are accepted by the Examiner.
Specification
The disclosure filed on 10/07/2024 is accepted by the Examiner.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 10-16 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding claim 10, the originally filed application does not disclose “providing the body volume information and at least one of user health data, medical treatment data, or the image data to a second machine learning model; receiving adjusted body volume information from the second machine learning model”. This is a new matter rejection.
Regarding claims 11-16, they are rejected because they depend directly or indirectly from claim 10 and claim 10 is rejected.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-9 and 17-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. US 12125582 B2. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1-9 and 17-20 of the present application are anticipated by claims 1-20 of U.S. Patent No. US 12125582 B2.
Present Application
US 12125582 B2
1. A method of determining treatment for a patient, comprising:
obtaining an image of the patient or a part of the patient;
predicting body volume information based on the obtained image;
adjusting the predicted body volume information based on at least one of user health data, medical treatment data, or analysis of the image; and providing a recommendation for treating the patient based on the adjusted body volume information
11. A method of determining treatment for a patient, comprising:
obtaining an image of the patient;
using a machine learning model and the image to predict body volume information; adjusting the predicted body volume information based on at least one of user health data, medical treatment data, or analysis of the image; and providing a recommendation for treating the patient based on the adjusted body volume information
2. The method of claim 1, wherein the image comprises an exterior of a body of the patient
12. The method of claim 11, wherein the image comprises the exterior of the patient's body
3. The method of claim 1, wherein obtaining the image comprises taking a photograph with an image capturing device
15. The method of claim 11, wherein obtaining the image comprises taking a photograph with an image capturing device
4. The method of claim 3, wherein the patient takes the photograph
16. The method of claim 15, wherein the patient takes the photograph
5. The method of claim 3, wherein the photograph is taken in the visible light spectrum having an
electromagnetic wavelength between about 400 nanometers and about 700 nanometers
17. The method of claim 15, wherein the photograph of the patient is taken in the visible light spectrum having an electromagnetic wavelength between about 400 nanometers and about 700 nanometers
6. The method of claim 1, wherein the body volume information comprises a body max index of the patient
19. The method of claim 11, wherein the information extracted from the image includes a body max index of the patient
7. The method of claim 1, wherein the body volume information
comprises a body volume index of the patient
18. The method of claim 11, wherein the information extracted from the image includes body volume information of the patient
8. The method of claim 1, wherein predicting body volume information based on the obtained image comprises
using a machine learning model and the obtained image to predict the body volume information
11….
using a machine learning model and the image to predict body
volume information
9. The method of claim 8, wherein the machine learning model comprises a body volume model
11…
using a machine learning model and the image to predict body volume information
17. An apparatus comprising: a processor; and computer readable medium containing programming instructions that, when executed, will cause the processor to:
receive body volume information, wherein the body volume information has been predicted using one or more images of a subject or part of a subject;
receive at least one of user health data, medical treatment data, analysis of one or more images of the subject, or one or more images of the subject;
adjust the body volume information based on at least one of the user health data, the medical treatment data, the analysis of one or more images of the subject, or the one or more images of the subject; and
transmit the adjusted body volume information to a medical treatment system for use in providing a recommendation for treating the subject
6. An apparatus comprising:
a processor; and computer readable medium containing programming instructions that, when executed, will cause the processor to:
receive user body volume data from a user device via a communication link;
adjust the user body volume data based on at least one of user health data, medical treatment data, or analysis of one or more images of a subject of the user device;
adjust a medical treatment plan based on the adjusted user body volume data; and
transmit the adjusted medical treatment to the user device
18. The apparatus of claim 17, wherein the body volume information comprises one or more of: body fat, body mass, or bone mineral density
9. The apparatus of claim 6, wherein the user body volume data comprises one or more of: body fat, body mass, or bone mineral density
19. The apparatus of claim 17, wherein the body volume information comprises a distribution of body fat
10. The apparatus of claim 6, wherein the user body volume data comprises a distribution of body fat
20. The apparatus of claim 17, wherein the body volume information comprises a change of body volume over a period of time
8. The apparatus of claim 6, wherein the user body volume data includes a
change of body volume over a period of time
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Aoun (US 20220101989 A1) discloses customized medical treatment.
Bharmi (US 20210020294 A1) discloses methods, devices and systems for holistic integrated healthcare patient management.
Shin (US 20220301171 A1) discloses apparatus for providing evaluation of bedsore stages and treatment recommendations using artificial intelligence and operation method thereof.
Wu (US 20220013230 A1) discloses training method for giving treatment recommendations to a physician based on a propensity score and an outcome score.
Batch (US 20050119914 A1) discloses system and method for analyzing medical treatment data.
De Vries (US 20230170065 A1) discloses treatment recommendation.
Goede (US 20220037018 A1) discloses automatically determining a medical recommendation for a patient based on multiple medical images from multiple different medical imaging modalities.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JUAN A TORRES whose telephone number is (571) 272-3119. The examiner can normally be reached M-F 9-5.
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, Kenneth N Vanderpuye can be reached at (571) 272-3078. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JUAN A TORRES/ Primary Examiner, Art Unit 2634
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