Using Machine Learning to Predict Antidepressant Treatment Outcome From Electronic Health Records

Abstract

Highlights Longitudinal questionnaire data were used to measure antidepressant treatment outcome. Machine learning models were used to predict outcome from electronic health records. The gradient boosting decision tree model achieved the best predictive results. Diagnostic codes and baseline severity were strong predictors of treatment outcome.