Machine Learning in Neurological and Psychiatric Disorders

Machine Learning in Neurological and Psychiatric Disorders: A Promising Approach for Clinical Assessment and Prediction Call for Papers Machine learning techniques have emerged as a promising approach in clinical neuroscience. Most imaging data is highly complex with subtle features reflecting the underlying complexity of the human brain, as well as the complexity of the spatial and temporal dynamical feature changes associated with neurological and psychiatric disorders. It has become increasingly evident that relying on simple approaches, such as peak activation, EEG epileptic spikes, region of interest analysis, is not sufficient to provide the outcome needed to explore the complexity of disease-related pathological alterations of brain functions and to accurately and reliably diagnose and classify neurological and psychiatric disorders. Furthermore, effective treatments for many of these disorders require early detection and…


Link to Full Article: Machine Learning in Neurological and Psychiatric Disorders