Published in
Wiley Open Access, Psychiatric Research & Clinical Practice, 4(5), p. 118-125, 2023
DOI: 10.1176/appi.prcp.20220015
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Using Machine Learning to Predict Antidepressant Treatment Outcome From Electronic Health Records
Journal article published in 2023 by
Zhenxing Xu,
Veer Vekaria 
,
Fei Wang,
Judith Cukor,
Chang Su,
Prakash Adekkanattu,
Pascal Brandt,
Guoqian Jiang,
Richard C. Kiefer,
Yuan Luo,
Luke V. Rasmussen,
Jie Xu,
Yunyu Xiao,
George Alexopoulos,
Jyotishman Pathak
,
Fei Wang,
Judith Cukor,
Chang Su,
Prakash Adekkanattu,
Pascal Brandt,
Guoqian Jiang,
Richard C. Kiefer,
Yuan Luo,
Luke V. Rasmussen,
Jie Xu,
Yunyu Xiao,
George Alexopoulos,
Jyotishman Pathak
This paper is made freely available by the publisher.
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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.