Abstract
Relapses and recurrences contribute to the significant morbidity and mortality in Major Depressive Disorder (MDD). Recent advances in mobile technologies and wearable sensors have enabled continuous remote monitoring of patients with MDD. Here we discuss the replication results of personalized (N of 1) relapse prediction framework using actigraphy data and self-reported symptoms to predict relapse and recurrence in MDD.
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