METHOD OF CREATING ZERO-BURDEN DIGITAL BIOMARKERS FOR DISORDERS, AND EXPLOITING CO-MORBIDITY PATTERNS TO DRIVE EARLY INTERVENTION

摘要

A diagnosis prediction (DP) computing device (102) receives training datasets from a health records server (108A), an insurance claims server (108B), and other third party servers (108C). DP computing device builds a model based on the training datasets and stores the model on a database (106) via a database server (104). Using the model and a stochastic learning algorithm, a risk estimator (110) determines a prediction of a disease or disorder diagnosis of a patient to a client device (112). The prediction is based on data gathered pertaining to the patient including unprocessed raw data comprising records of diagnostic codes generated during past medical encounters from an insurance claims database.