Granted Patent B1

US 12,073,930 · App. 18/536,623 · Granted Aug 27, 2024

Inventor: Steven David Alperin (New York, NY)

Assignee: SurvivorNet, Inc.

G16H15/00G06N20/00

Abstract

Claims (54)

1. An apparatus for generating a user report, wherein the apparatus comprises:

at least a processor; and

a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to:

receive a user profile from a user;

generate a first set of inquiries as a function of the user profile using an inquiry machine learning model, wherein generating the first set of inquiries comprises:

generally training the inquiry machine learning model using non-user specific training data;

specifically training, after generally training, the inquiry machine learning model using inquiry training data, wherein the inquiry training data comprises a plurality of user profiles as inputs correlated to sets of inquiries as outputs, wherein specifically training further comprises:

updating the inquiry training data as a function of past inputs and correlated past outputs;

generating an accuracy score as a function of user feedback; and

retraining the inquiry machine learning model as a function of the updated inquiry training data and the accuracy score; and

generating the first set of inquiries as a function of the user profile using the trained inquiry machine learning model;

receive a first set of inquiry responses from the user as a function of the first set of inquiries;

generate a user report as a function of the first set of inquiries and the first set of inquiry responses; and

display the user report using a display device.

2. The apparatus of claim 1 , wherein the inquiry machine learning model comprises a large language model.

3. The apparatus of claim 1 , wherein generally training the inquiry machine learning model using the non-user specific training data further comprises anonymizing the non-user specific training data using an anonymization process.

4. The apparatus of claim 1 , wherein generally training the inquiry machine learning model using the non-user specific training data further comprises placing the non-user specific training data through a verification process.

5. The apparatus of claim 1 , wherein the memory contains instructions further configuring the at least a processor to:

determine a confidence score as a function the user report; and

compare the confidence score to a confidence threshold.

6. The apparatus of claim 5 , wherein the memory contains instructions further configuring the at least a processor to:

generate a second set of inquiries as a function of the comparison of the confidence score to the confidence threshold;

receive a second set of inquiry responses from the user; and

refine the user report as a function of the second set of inquiries and the second set of inquiry responses.

7. The apparatus of claim 1 , wherein the user report comprises a plurality of diagnostic data.

8. The apparatus of claim 1 , wherein the user report comprises a treatment plan.

9. The apparatus of claim 1 , wherein receiving the first set of inquiry responses comprises receiving the first set of inquiry responses from at least a sensor.

10. The apparatus of claim 1 , wherein the memory contains instructions further configuring the at least a processor to generate a plurality of contextual user data as a function of the user profile.

11. A method for generating a user report, wherein the method comprises:

receiving, using at least a processor, a user profile from a user;

generating, using the at least a processor, a first set of inquiries as a function of the user profile using an inquiry machine learning model, wherein generating the first set of inquiries comprises:

generally training the inquiry machine learning model using non-user specific training data;

specifically training, after generally training, the inquiry machine learning model using inquiry training data, wherein the inquiry training data comprises a plurality of user profiles as inputs correlated to sets of inquiries as outputs, wherein specifically training further comprises:

updating the inquiry training data as a function of past inputs and correlated past outputs;

generating an accuracy score as a function of user feedback; and

retraining the inquiry machine learning model as a function of the updated inquiry training data and the accuracy score; and

generating the first set of inquiries as a function of the user profile using the trained inquiry machine learning model;

receiving, using the at least a processor, a first set of inquiry responses from the user as a function of the first set of inquiries;

generating, using the at least a processor, a user report as a function of the first set of inquiries and the first set of inquiry responses; and

displaying the user report using at least a display device.

12. The method of claim 11 , wherein the inquiry machine learning model comprises a large language model.

13. The method of claim 11 , wherein the user profile comprises a plurality of biological data associated with the user.

14. The method of claim 11 , wherein the method further comprises:

determining, using the at least a processor, a confidence score as a function the user report; and

comparing, using the at least a processor, the confidence score to a confidence threshold.

15. The method of claim 14 , wherein the method further comprises:

generating, using the at least a processor, a second set of inquiries as a function of the comparison of the confidence score to the confidence threshold;

receiving, using the at least a processor, a second set of inquiry responses from the user; and

refining, using the at least a processor, the user report as a function of the second set of inquiries and the second set of inquiry responses.

16. The method of claim 11 , wherein the method further comprises presenting, using the at least a processor, the first set of inquiries to the user using a chatbot.

17. The method of claim 11 , wherein the user report comprises a plurality of diagnostic data.

18. The method of claim 11 , wherein the user report comprises a treatment plan.

19. The method of claim 11 , wherein the method further comprises receiving, using the at least a processor, the first set of inquiry responses from at least a sensor.

20. The method of claim 11 , wherein the method further comprises generating, using the at least a processor, a plurality of contextual user data as a function of the user profile.

Assignments (1)

Cited By (8)

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