Clustered analysis of training scenarios for addressing neurodevelopmental disorders

A computing device comprising:

• one or more processors;
• and
• memory storing instructions that, when executed by the one or more processors, cause the computing device to:
• receive population data that indicates a plurality of different subject subpopulations;
• receive skill data that indicates a plurality of different skills associated with one or more behaviors exhibited by individuals with one or more neurodevelopmental disorders;
• identify, based on the population data and the skill data, behavioral goals for each subject subpopulation of the plurality of different subject subpopulations, wherein the behavioral goals correspond to one or more commonly-unattained skills for each subject subpopulation of the plurality of different subject subpopulations;
• generate scenario data which indicates a plurality of different training scenarios for training one or more skills of the plurality of different skills;
• generate efficacy data by estimating, for each training scenario of the plurality of different training scenarios, a probability that each skill of the plurality of different skills can be trained by the training scenario;
• generate estimated clinical success data by simulating, for each training scenario of the plurality of different training scenarios and for each subject subpopulation of the plurality of different subject subpopulations, a degree of behavioral change by the subject subpopulation;
• and
• select, based on the behavioral goals, the efficacy data, and the estimated clinical success data, a combination of a first subject subpopulation of the plurality of different subject subpopulations and a first training scenario of the plurality of different training scenarios, wherein the first training scenario of the plurality of different training scenarios is associated with training two or more of the plurality of different skills.

One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause a computing device to:

• receive population data that indicates a plurality of different subject subpopulations;
• receive skill data that indicates a plurality of different skills associated with one or more behaviors exhibited by individuals with one or more neurodevelopmental disorders;
• identify, based on the population data and the skill data, behavioral goals for each subject subpopulation of the plurality of different subject subpopulations, wherein the behavioral goals correspond to one or more commonly-unattained skills for each subject subpopulation of the plurality of different subject subpopulations;
• generate scenario data which indicates a plurality of different training scenarios for training one or more skills of the plurality of different skills;
• generate efficacy data by estimating, for each training scenario of the plurality of different training scenarios, a probability that each skill of the plurality of different skills can be trained by the training scenario;
• generate estimated clinical success data by simulating, for each training scenario of the plurality of different training scenarios and for each subject subpopulation of the plurality of different subject subpopulations, a degree of behavioral change by the subject subpopulation;
• and
• select, based on the behavioral goals, the efficacy data, and the estimated clinical success data, a combination of a first subject subpopulation of the plurality of different subject subpopulations and a first training scenario of the plurality of different training scenarios, wherein the first training scenario of the plurality of different training scenarios is associated with training two or more of the plurality of different skills.