Granted Patent B1

US 12,443,421 · App. 19/191,391 · Granted Oct 14, 2025

Inventors: Blake Browder (Dallas, TX); Joy Figarsky (Little Rock, AR)

Assignee: Signet Health Corporation

G06F9/451G06F9/542G06F2209/544

Abstract

Claims (50)

1. An apparatus for generating an interactive graphical user interface, the apparatus comprising:

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 first input data and second input data;

identify, using the at least a processor, at least a target datum from the first input data;

determine, using the at least a processor, at least an operating parameter from the second input data as a function of the at least a target datum;

generate, using a task machine-learning model, a plurality of tasks as a function of the at least an operating parameter; and

generate, using the at least a processor, an interactive graphical user interface as a function of the plurality of tasks, wherein:

each task node represents one task of the plurality of tasks and each task node comprises an input event handler of a plurality of input event handler; and

generating the interactive graphical user interface comprises:

identifying an interaction pattern as a function of user actions using an interaction pattern machine-learning model trained on training data comprising historical user action data; and

generating the interactive graphical user interface as a function of the interaction pattern.

2. The apparatus of claim 1 , wherein generating the plurality of tasks comprises:

generating task training data, wherein the task training data comprises exemplary operating parameters correlated to exemplary tasks;

training the task machine-learning model using the task training data, wherein the task machine-learning model comprises a language processing module; and

generating the plurality of tasks using the trained task machine-learning model.

3. The apparatus of claim 2 , wherein the at least a processor is further configured to iteratively update, using a feedback loop, the task training data.

4. The apparatus of claim 1 , wherein the at least an operating parameter comprises at least a compliance threshold associated with the target datum.

5. The apparatus of claim 1 , wherein the at least a processor generates each task of the plurality of tasks based on a facility cohort using a machine-learning module.

6. The apparatus of claim 1 , wherein generating the interactive graphical user interface comprises:

receiving concurrent user actions at least partially through one of the plurality of input event handlers for the plurality of task nodes from a plurality of user devices; and

updating the interactive graphical user interface as a function of the concurrent user actions using an adaptive mechanism.

7. The apparatus of claim 6 , wherein the adaptive mechanism is configured to evaluate user action of the concurrent user actions wherein evaluating the user action comprises one or more of accepting, modifying, and the user action.

8. The apparatus of claim 6 , wherein updating the interactive graphical user interface comprises updating the interactive graphical user interface as a function of interaction timestamps of the concurrent user actions using the adaptive mechanism.

9. The apparatus of claim 6 , wherein updating the interactive graphical user interface comprises updating the interactive graphical user interface as a function of user functions using the adaptive mechanism.

10. The apparatus of claim 1 , wherein the plurality of tasks comprise data-gathering activities.

11. A method for generating an interactive graphical user interface, the method comprising:

receiving, using at least a processor, first input data and second input data;

identifying, using the at least a processor, at least a target datum from the first input data;

determining, using the at least a processor, at least an operating parameter from the second input data as a function of the at least a target datum;

generating, using a task machine-learning model, a plurality of tasks as a function of the at least an operating parameter; and

generating, using the at least a processor, an interactive graphical user interface as a function of the plurality of tasks, wherein:

each task node represents one task of the plurality of tasks and each task node comprises an input event handler of a plurality of input event handler; and

generating the interactive graphical user interface comprises:

identifying an interaction pattern as a function of user actions using an interaction pattern machine-learning model trained on training data comprising historical user action data; and

generating the interactive graphical user interface as a function of the interaction pattern.

12. The method of claim 11 , wherein generating the plurality of tasks comprises:

generating task training data, wherein the task training data comprises exemplary operating parameters correlated to exemplary tasks;

training the task machine-learning model using the task training data, wherein the task machine-learning model comprises a language processing module; and

generating the plurality of tasks using the trained task machine-learning model.

13. The method of claim 12 , further comprising iteratively updating, using a feedback loop, the task training data.

14. The method of claim 11 , wherein the at least an operating parameter comprises at least a compliance threshold associated with the target datum.

15. The method of claim 11 , further comprising generating, using the at least a processor, each task of the plurality of tasks based on a facility cohort using a machine-learning module.

16. The method of claim 11 , wherein generating the interactive graphical user interface comprises:

receiving concurrent user actions at least partially through one of the plurality of input event handlers for the plurality of task nodes from a plurality of user devices; and

updating the interactive graphical user interface as a function of the concurrent user actions using an adaptive mechanism.

17. The method of claim 16 , wherein the adaptive mechanism is configured to evaluate user action of the concurrent user actions wherein evaluating the user action comprises one or more of accepting, modifying, and the user action.

18. The method of claim 16 , wherein updating the interactive graphical user interface comprises updating the interactive graphical user interface as a function of interaction timestamps of the concurrent user actions using the adaptive mechanism.

19. The method of claim 16 , wherein updating the interactive graphical user interface comprises updating the interactive graphical user interface as a function of user functions using the adaptive mechanism.

20. The method of claim 11 , wherein the plurality of tasks comprise data-gathering activities.

Assignments (3)

Continuity (1)

References Cited (15)