Predicting clinically meaningful changes in behavioral health symptomatology using patient voice inputs

Abstract

One example method for predicting clinically meaningful changes in behavioral health symptomatology using patient voice inputs includes receiving a baseline behavioral sample indicating an initial behavioral health symptomatology of an individual; receiving a subsequent behavioral sample including a supplemental voice recording from the individual; computing a difference score from a trained machine-learning ('ML') model by providing the baseline behavioral sample and the subsequent behavioral sample as input to the trained ML model wherein the difference score indicates a predicted change in behavioral health symptomatology of the individual, the trained ML model being configured to output a score indicating a predicted change in behavioral health symptomatology based on input data; and outputting the predicted change in behavioral health symptomatology to a client device executing a graphical user interface indicating the change for an entity treating the individual.