A Survey of Machine Learning Based Approaches for Neurological Disorder Predictions

Abstract

Novel computational tools based on ML schemes are useful in knowing the complex brain functions and its diseases. It was found during the study that differentiation among various neurological disorders is not easy task due to similarities in symptoms. This paper significantly examines and compares performances of many ML based methods to diagnose neurological illness—emphasized on Alzheimer's disease, Parkinson's disease and schizophrenia. The article provides the overview of computational intelligence methods evaluates and diverse performance metrics used to predict neurological disorders from different type of data.