Granted Patent B1

US 12,518,452 · App. 18/963,452 · Granted Jan 6, 2026

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

Assignee: Behavioral Health Operations, LLC

G06T11/60G06F9/451G06N3/08G06T2200/24

Abstract

Claims (75)

1 . An apparatus for a graphical interface with a dual-layer component, the apparatus comprising:

at least a processor; and

a non-transitory memory communicatively connected to the at least a processor, the non-transitory memory containing instructions configuring the at least a processor to:

generate a content list data structure comprising a data structure enumerating and/or listing a plurality of elements of data to be conveyed using user interface elements and/or modules based on at least an element of initial data using a trained content list structure neural network, wherein training the content list structure neural network comprises:

receiving training data correlating content list data structure inputs to content list data structure examples, wherein the content list data structure examples;

receiving feedback indicated a validity of a generated content list data structure generated using the trained content list structure neural network;

update the training data as a function of the received feedback;

retrain the content list structure neural network as a function of the updated training data;

identify, using the content list data structure generated using the retrained content list structure neural network, a plurality of display configuration modules,

wherein the plurality of display configuration modules includes:

a streaming module; and

a dialog module; and

configure a remote device to generate a plurality of display fields, each display field producing an output from an interface-level component of a plurality of interface-level components, wherein the plurality of display fields includes:

a first display field configured to display an output of the streaming module; and

a second display field configured to display an output of the dialog module and receive and input to the dialog module,

wherein generating the content list data structure further comprises:

determining a plurality of overlapping geographical constraints of the remote device; and

generating the content list data structure using the plurality of overlapping geographical constraints, wherein a geographical constraint comprises a geographical region and/or location associated with a computing device.

2 . The apparatus of claim 1 , wherein generating the content list data structure further comprises:

transmitting a query to at least a third-party device based on the initial data;

receiving textual data from the at least a third-party device; and

generating the content list data structure using the textual data.

3 . The apparatus of claim 2 , wherein the at least a third-party device further comprises a plurality of third-party devices, and generating the content list data structure further comprises:

determining a first geographical constraint of the remote device;

determining a second geographical constraint of a selected third-party device of the plurality of third-party devices; and

generating the content list data structure using textual data received from the selected third-party device.

4 . The apparatus of claim 3 , wherein determining the first geographical constraint further comprises:

training a geographical constraint neural network using training data correlating device data examples to geographical constraint data;

detecting device data of the remote device; and

determining the first geographical constraint using the device data and the geographical constraint neural network.

5 . The apparatus of claim 1 , wherein generating the content list data structure further comprises:

receiving an input from the remote device; and

generating the content list data structure using the input.

6 . The apparatus of claim 1 , wherein generating the content list data structure further comprises generating the content list data structure using a trained content list data structure neural network.

7 . The apparatus of claim 1 , wherein identifying the plurality of display configuration modules further comprises identifying the plurality of display configuration modules using a display configuration neural network.

8 . The apparatus of claim 1 , wherein the dialog module further comprises a chatbot.

9 . The apparatus of claim 1 further configured to:

generate an output of the content list data structure; and

configure the remote device to display the generated output.

10 . A method of generating a graphical interface with a dual-layer component, the method comprising:

generating, by at least a processor, a content list data structure comprising a data structure enumerating and/or listing a plurality of elements of data to be conveyed using user interface elements and/or modules based on at least an element of initial data using a trained content list structure neural network, wherein training the content list structure neural network comprises:

receiving training data correlating content list data structure inputs to content list data structure examples, wherein the content list data structure examples;

receiving feedback indicated a validity of a generated content list data structure generated using the trained content list structure neural network;

update the training data as a function of the received feedback;

retrain the content list structure neural network as a function of the updated training data;

identifying, by the at least a processor and using the content list data structure generated using the retrained content list structure neural network, a plurality of display configuration modules, wherein the plurality of display configuration modules includes:

a streaming module; and

a dialog module; and

configuring, by the at least a processor, a remote device to generate a plurality of display fields, each display field producing an output from an interface-level component of a plurality of interface-level components, wherein the plurality of display fields includes:

a first display field configured to display an output of the streaming module; and

a second display field configured to display an output of the dialog module and receive and input to the dialog module,

wherein generating the content list data structure further comprises:

determining a plurality of overlapping geographical constraints of the remote device; and

generating the content list data structure using the plurality of overlapping geographical constraints, wherein a geographical constraint comprises a geographical region and/or location associated with a computing device.

11 . The method of claim 10 , wherein generating the content list data structure further comprises:

transmitting a query to at least a third-party device based on the initial data;

receiving textual data from the at least a third-party device; and

generating the content list data structure using the textual data.

12 . The method of claim 11 , wherein the at least a third-party device further comprises a plurality of third-party devices, and generating the content list data structure further comprises:

determining a first geographical constraint of the remote device;

determining a second geographical constraint of a selected third-party device of the plurality of third-party devices; and

generating the content list using textual data received from the selected third-party device.

13 . The method of claim 12 , wherein determining the first geographical constraint further comprises:

training a geographical constraint neural network using training data correlating device data examples to geographical constraint data;

detecting device data of the remote device; and

determining the first geographical constraint using the device data and the geographical constraint neural network.

14 . The method of claim 10 , wherein generating the content list data structure further comprises:

receiving an input from the remote device; and

generating the content list data structure using the input.

15 . The method of claim 10 , wherein generating the content list data structure further comprises generating the content list data structure using a trained content list data structure neural network.

16 . The method of claim 10 , wherein identifying the plurality of display configuration modules further comprises identifying the plurality of display configuration modules using a display configuration neural network.

17 . The method of claim 10 , wherein the dialog module further comprises a chatbot.

18 . The method of claim 10 further comprising:

generating an output of the content list data structure; and

configuring the remote device to display the generated output.

Assignments (3)

References Cited (13)