Granted Patent B1

US 12,524,727 · App. 18/957,727 · Granted Jan 13, 2026

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

Assignee: Behavioral Health Operations, LLC

G06Q10/067G06Q10/06375G06Q30/018G16H40/20

Abstract

Claims (74)

1 . A method for displaying and modifying assessment data through a graphical user interface (GUI), the method comprising:

receiving, by a computing device, input data objects;

generating, by the computing device, through an assessment module, simulated assessment data sets;

generating, by the computing device, an assessment score of the input data objects and simulated assessment data sets as a function of a machine-learning algorithm; and

modifying, by the computing device, a GUI based on the input data objects and the assessment score, wherein modifying the GUI comprises:

automatically generating context-sensitive command inputs that trigger analysis routines within the GUI based on at least a geographic location received from the input data objects;

reconfiguring the GUI to adjust a display hierarchy of interactive elements based on the assessment score;

evaluating, using a rule-based algorithm, compliance associated with the input data objects;

training a machine learning model in accordance with at least one of: historical data and compliance data;

predicting, using the trained machine learning model, a compliance outcome associated with the input data objects; initiating a simulation module configured to run multiple hypothetical modification scenarios associated with the input data objects, predict assessment scores for each scenario using the machine learning model, and iteratively identify facility modifications that maximize the assessment score;

filtering, using an autoencoder comprising an unsupervised neural network using at least one of: dimensionality reduction and denoising, the input data objects;

compressing, using an encoder associated with the autoencoder, the input data objects;

reconstructing, using a decoder associated with the autoencoder, the input data objects from the compressed input data objects;

wherein the GUI updates to present an optimized compliance outcome and

configures a display device, using the reconfigured GUI to initiate the simulation module.

2 . The method of claim 1 , wherein receiving the input data objects comprises employing a machine vision system configured to extract visual inputs from image data of an environment from the input data objects.

3 . The method of claim 2 , further comprising:

classifying the visual inputs; and

converting the visual inputs into structured environmental data for further processing by the assessment module.

4 . The method of claim 1 , wherein receiving the input data objects comprises implementing Application Programming Interfaces (APIs) configured to:

send a request to an external endpoint based on a geographic location of a facility; and

obtain structured data from third-party platforms for further processing by the assessment module.

5 . The method of claim 1 , wherein the at least a processor is further configured to implement a geographical mapping module configured to:

receive the input data objects;

employ a geospatial analysis algorithm to map a facility's location based on the input data objects;

classifying the facility location to regulatory requirements; and

output regulatory requirements based on the facility's location.

6 . The method of claim 1 , wherein initiating a simulation comprises employing a grid-based layout algorithm to segment a facility into specific areas where modifications are to be modeled.

7 . The method of claim 1 , further comprising recalculating the assessment score based on a modification to the simulation received through user input.

8 . The method of claim 1 , wherein the GUI is further configured to display a heatmap using color-coded indicators to represent areas of compliance and non-compliance within a facility based on at least the assessment score, wherein generating the heatmap comprises:

processing the input data objects to identify environmental data;

calculating a plurality of compliance scored based on the environmental data; and

employing a grid-based layout algorithm to map a layout of the facility layout into a structured grid format, wherein each cell in the grid is assigned a compliance score.

9 . The method of claim 1 , wherein modifying the GUI based on the input data objects comprises employing an adaptive layout engine configured to automatically scale and adjust the GUI based on a display device such that the GUI is responsive across heterogeneous platforms.

10 . A method as claimed in claim 1 , further comprising:

imposing, by a constraint satisfaction algorithm operably communicative with the at least a processor, at least one limit associated with the input data objects.

11 . An apparatus comprising a graphical user interface (GUI) for displaying and modifying assessment data, the apparatus comprising:

at least a processor; and

a memory configuring the at least a processor to:

receive input data objects;

generate, through an assessment module, simulated assessment data sets;

generate an assessment score of the input data objects and simulated assessment data sets as a function of a machine-learning algorithm; and

modify a GUI based on the input data objects and the assessment score, wherein modifying the GUI comprises:

automatically generating context-sensitive command inputs that trigger analysis routines within the GUI based on at least a geographic location received from the input data objects;

reconfiguring the GUI to adjust a display hierarchy of interactive elements based on the assessment score;

evaluating, using a rule-based algorithm, compliance associated with the input data objects;

training a machine learning model in accordance with at least one of: historical data and compliance data;

predicting, using the trained machine learning model, a compliance outcome associated with the input data objects; initiating a simulation module configured to run multiple hypothetical modification scenarios associated with the input data objects, predict assessment scores for each scenario using the machine learning model, and iteratively identify facility modifications that maximize the assessment score;

filtering, using an autoencoder comprising an unsupervised neural network using at least one of: dimensionality reduction and denoising, the input data objects;

compressing, using an encoder associated with the autoencoder, the input data objects;

reconstructing, using a decoder associated with the autoencoder, the input data objects from the compressed input data objects;

wherein the GUI updates to present an optimized compliance outcome and

configures a display device, using the reconfigured GUI to initiate the simulation module.

12 . The apparatus of claim 11 , wherein receiving the input data objects comprises employing a machine vision system configured to extract visual inputs from image data of an environment from the input data objects.

13 . The apparatus of claim 12 , wherein the at least a processor is further configured to:

classify the visual inputs; and

convert the visual inputs into structured environmental data for further processing by the assessment module.

14 . The apparatus of claim 11 , wherein receiving the input data objects comprises implementing Application Programming Interfaces (APIs) configured to:

send a request to an external endpoint based on a geographic location of a facility; and

obtain structured data from third-party platforms for further processing by the assessment module.

15 . The apparatus of claim 11 , wherein the at least a processor is further configured to implement a geographical mapping module configured to:

receive the input data objects;

employ a geospatial analysis algorithm to map a facility's location based on the input data objects;

classifying the facility location to regulatory requirements; and

output regulatory requirements based on the facility's location.

16 . The apparatus of claim 11 , wherein initiating a simulation comprises employing a grid-based layout algorithm to segment a facility into specific areas where modifications are to be modeled.

17 . The apparatus of claim 11 , further comprising recalculating the assessment score based on a modification to the simulation received through user input.

18 . The apparatus of claim 11 , wherein the GUI is further configured to display a heatmap using color-coded indicators to represent areas of compliance and non-compliance within a facility based on at least the assessment score, wherein generating the heatmap comprises:

processing the input data objects to identify environmental data;

calculating a plurality of compliance scored based on the environmental data; and

employing a grid-based layout algorithm to map a layout of the facility layout into a structured grid format, wherein each cell in the grid is assigned a compliance score.

19 . The apparatus of claim 11 , wherein modifying the GUI based on the input data objects comprises employing an adaptive layout engine configured to automatically scale and adjust the GUI based on a display device such that the GUI is responsive across heterogeneous platforms.

20 . An apparatus as claimed in claim 11 , further comprising:

a constraint satisfaction algorithm, operably communicative with the at least a processor, for imposing at least one limit associated with the input data objects.

Assignments (3)

References Cited (26)