Development and validation of a multimodal neuroimaging biomarker for electroconvulsive therapy outcome in depression: a multicenter machine learning analysis.

Willem Benjamin BruinLeif OltedalHauke BartschChristopher AbbottMiklos ArgyelanTracy BarbourJoan CamprodonSamadrita ChowdhuryRandall EspinozaPeter MuldersKatherine NarrMardien OudegaDidi RhebergenFreek Ten DoesschateIndira TendolkarPhilip van EijndhovenEric van ExelMike van VerseveldBenjamin WadeJeroen van WaardePaul ZhutovskyAnnemiek DolsGuido van Wingen

Published in: Psychological medicine (2023)

These results show that multimodal neuroimaging data can be used to predict remission with ECT for individual patients across different treatment centers, despite significant variability in clinical characteristics across centers. Future development of a clinical decision support tool applying these biomarkers may be feasible.

Keyphrases

clinical decision support
machine learning
electronic health record
ejection fraction
pain management
newly diagnosed
big data
depressive symptoms
artificial intelligence
clinical trial
cross sectional
patient reported outcomes
current status
ulcerative colitis
disease activity