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Machine learning using multimodal clinical,electroencephalographic, and magnetic resonance imaging data can predict incident depression in adults with epilepsy: A pilot study |
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| Authors: | Guillermo Delgado-García Jordan D. T. Engbers Samuel Wiebe Pauline Mouches Kimberly Amador Nils D. Forkert James White Tolulope Sajobi Karl Martin Klein Colin B. Josephson the Calgary Comprehensive Epilepsy Program Collaborators |
| Affiliation: | 1. Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada;2. Desid Labs, Calgary, Alberta, Canada;3. Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada;4. Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada;5. Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada Libin Cardiovascular Institute, University of Calgary, Calgary, Alberta, Canada Department of Cardiac Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada |
| Abstract: | |
| Keywords: | depression EEG epilepsy machine learning MRI prediction |