228. Assessing the Predictive Utility of Quantitative Electroencephalography Coherence in Adolescent Major Depressive Disorder: A Machine Learning Approach

Journal article

Peer reviewed

Maia Gersten, Benjamin Wade, Farren Briggs, Kenneth Loparo, Farhad Kaffashi, Asif Jamil, Oscar Morales, Paolo Cassano and Molly McVoy

Biological psychiatry (1969), Vol.97(9), pp.S189-S189

2025-05-01

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Title: 228. Assessing the Predictive Utility of Quantitative Electroencephalography Coherence in Adolescent Major Depressive Disorder: A Machine Learning Approach
Creators: Maia Gersten - Harvard Medical School
Benjamin Wade - Harvard Medical School
Farren Briggs - University of Miami
Kenneth Loparo - Case Western Reserve University
Farhad Kaffashi - Case Western Reserve University
Asif Jamil - Harvard Medical School
Oscar Morales - Harvard Medical School
Paolo Cassano - Harvard Medical School
Molly McVoy - Case Western Reserve University
Publication Details: Biological psychiatry (1969), Vol.97(9), pp.S189-S189
Publisher: Elsevier Inc
Academic Unit: Miller School of Medicine; UMMG Department of Public Health Sciences Research
Language: English
Resource Type: Journal article
Record Identifier: 991032796209002976