System and method for customized patient resources and behavior phenotyping

A system, comprising:

• a video capture device;
• a processor;
• and
• a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising:
• receiving training data sets describing relationships between:
• (1) patients diagnosed with a physical illness, (2) patient health risk levels, and (3) patient trajectories without intervention;
• training a neural network using the training data sets, resulting in a machine learning algorithm;
• receiving, from a mobile device, answers to a behavioral questionnaire, wherein the answers are received in real-time as a patient self-reports answers to the behavioral questionnaire on the mobile device
• recording, via the video capture device, a video of the patient as the answers are completed;
• identifying, based on the video of the patient, at least one facial expression of the patient made during completion of the behavioral questionnaire;
• identifying, based on the video of the patient, at least one repeated body posture of the patient made during completion of the behavioral questionnaire;
• calculating a time period between instances of the at least one repeated body posture;
• calculating a numerical score of the patient based upon the answers to the behavioral questionnaire, the time period, the at least one repeated body posture, and the at least one facial expression of the patient made during completion of the behavioral questionnaire;
• receiving a physical medical condition of the patient;
• and
• generating, by executing a playlist algorithm based on the physical medical condition of the patient using the physical medical condition of the patient and the numerical score, a playlist of videos associated with the physical medical condition
• receiving a record of which videos within the playlist of videos were watched by the patient;
• executing the machine learning algorithm, with inputs to the machine learning algorithm comprising the record and outputs of the machine learning algorithm comprising a modification to the playlist algorithm;
• and
• modifying the playlist algorithm according to the modification.

A non-transitory computer-readable storage medium having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising:

• receiving training data sets describing relationships between:
• (1) patients diagnosed with a physical illness, (2) patient health risk levels, and (3) patient trajectories without intervention;
• training a neural network using the training data sets, resulting in a machine learning algorithm;
• receiving, from a mobile device, answers to a behavioral questionnaire, wherein the answers are received in real-time as a patient self-reports answers to the behavioral questionnaire on the mobile device
• recording, via a video capture device, a video of the patient as the answers are completed;
• identifying, based on the video of the patient, at least one facial expression of the patient made during completion of the behavioral questionnaire;
• identifying, based on the video of the patient, at least one repeated body posture of the Patient made during completion of the behavioral questionnaire;
• calculating a time period between instances of the at least one repeated body posture;
• calculating a numerical score of the patient based upon the answers to the behavioral questionnaire, the time period, the at least one repeated body posture, and the at least one facial expression of the patient made during completion of the behavioral questionnaire;
• receiving a physical medical condition of the patient;
• and
• generating, by executing a playlist algorithm based on the physical medical condition of the patient using the physical medical condition of the patient and the numerical score, a playlist of videos associated with the physical medical condition;
• receiving a record of which videos within the playlist of videos were watched by the patient;
• executing the machine learning algorithm, with inputs to the machine learning algorithm comprising the record and outputs of the machine learning algorithm comprising a modification to the playlist algorithm;
• and
• modifying the playlist algorithm according to the modification.