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Get Free AccessMachine 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 leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (n=5,356) to provide a generalizable ML classification benchmark of major depressive disorder (MDD). Using brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD vs healthy controls (HC) with around 62% balanced accuracy, but when harmonizing the data using ComBat balanced accuracy dropped to approximately 52%. Similar results were observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may achieve more encouraging prospects.
V. Belov, Tracy Erwin-Grabner, Ali Saffet Gönül, Alyssa R. Amod, Amar Ojha, André Alemán, Annemiek Dols, Anouk Scharntee, Aslihan Uyar-Demir, Ben J. Harrison, Benson M. Irungu, Bianca Besteher, Bonnie Klimes‐Dougan, Brenda W.J.H. Penninx, Bryon A. Mueller, Carlos A. Zarate, Christopher G. Davey, Christopher R. K. Ching, Colm G. Connolly, Cynthia H.Y. Fu, Dan Joseph Stein, Danai Dima, David E.J. Linden, David M. A. Mehler, Edith Pomarol‐Clotet, Elena Pozzi, Elisa Melloni, Francesco Benedetti, Frank P. MacMaster, Hans J. Grabe, Henry Völzke, Ian H. Gotlib, Jair C. Soares, Jennifer W. Evans, Kang Sim, Katharina Wittfeld, Kathryn R. Cullen, Liesbeth Reneman, Mardien L. Oudega, Margaret J. Wright, Marı́a J. Portella, Matthew D. Sacchet, Meng Li, Moji Aghajani, Mon-Ju Wu, Natalia Jaworska, Neda Jahanshad, Nic J.A. van der Wee, Nynke A. Groenewold, J. Paul Hamilton, Philipp G. Saemann, Robin Bülow, Sara Poletti, Sarah Whittle, Sophia I. Thomopoulos, Steven J. A. van, der Werff, Sheri‐Michelle Koopowitz, T. Lancaster, Tiffany C. Ho, Tony T. Yang, Zeynep Başgöze, Dick J. Veltman, Lianne Schmaal, Paul M. Thompson, Roberto Goya‐Maldonado (2022). Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures. , DOI: https://doi.org/10.48550/arxiv.2206.08122.
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Type
Preprint
Year
2022
Authors
66
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.48550/arxiv.2206.08122
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