Abstract: A management platform for characterizing one or more neuropsychiatric and/or neurological disorders of a patient based on received assessment data and heuristic data, which is employed to generate a diagnosis, goals and therapies for the patient. Machine learning models are used to optimize the diagnosis, personalized goals, and therapies provided for the patient. Different types of assessment data may include: layperson data, clinical data, biometric data, video data, medical data, heuristic data, or the like. Also, different types of the assessment data may be weighted differently.

Abstract: Method for managing treatment for a disorder of a patient that employs instructions to generate an interview dataset and a behavior detection dataset associated with a patient. The interview dataset is employed to provide tasks for the patient to perform while monitoring the patient for performance of different types of behaviors in the behavior detection dataset. The behavior detection dataset is transformed into an observation dataset based upon detection of monitored behaviors performed by the patient that corresponds to the behavior detection dataset. A characterization of the disorder of the patient is based upon the interview dataset and the observation dataset.