Machine learning using multimodal clinical, electroencephalographic, and magnetic resonance imaging data can predict incident depression in adults with epilepsy: A pilot study
Abstract:ObjectiveThis study was undertaken to develop a multimodal machine learning (ML) approach for predicting incident depression in adults with epilepsy.MethodsWe randomly selected 200 patients from the Calgary Comprehensive Epilepsy Program registry and linked their registry‐based clinical data to their first‐available clinical electroencephalogram (EEG) and magnetic resonance imaging (MRI) study. We excluded patients with a clinical or Neurological Disorders Depression Inventory for Epilepsy (NDDI‐E)‐based diagn… Show more
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