Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures

Abstract Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data l...

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Main Authors: Vladimir Belov, Tracy Erwin-Grabner, Moji Aghajani, Andre Aleman, Alyssa R. Amod, Zeynep Basgoze, Francesco Benedetti, Bianca Besteher, Robin Bülow, Christopher R. K. Ching, Colm G. Connolly, Kathryn Cullen, Christopher G. Davey, Danai Dima, Annemiek Dols, Jennifer W. Evans, Cynthia H. Y. Fu, Ali Saffet Gonul, Ian H. Gotlib, Hans J. Grabe, Nynke Groenewold, J Paul Hamilton, Ben J. Harrison, Tiffany C. Ho, Benson Mwangi, Natalia Jaworska, Neda Jahanshad, Bonnie Klimes-Dougan, Sheri-Michelle Koopowitz, Thomas Lancaster, Meng Li, David E. J. Linden, Frank P. MacMaster, David M. A. Mehler, Elisa Melloni, Bryon A. Mueller, Amar Ojha, Mardien L. Oudega, Brenda W. J. H. Penninx, Sara Poletti, Edith Pomarol-Clotet, Maria J. Portella, Elena Pozzi, Liesbeth Reneman, Matthew D. Sacchet, Philipp G. Sämann, Anouk Schrantee, Kang Sim, Jair C. Soares, Dan J. Stein, Sophia I. Thomopoulos, Aslihan Uyar-Demir, Nic J. A. van der Wee, Steven J. A. van der Werff, Henry Völzke, Sarah Whittle, Katharina Wittfeld, Margaret J. Wright, Mon-Ju Wu, Tony T. Yang, Carlos Zarate, Dick J. Veltman, Lianne Schmaal, Paul M. Thompson, Roberto Goya-Maldonado, the ENIGMA Major Depressive Disorder working group
Format: Article
Language:English
Published: Nature Portfolio 2024-01-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-47934-8

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