Machine Learning Techniques to Estimate Neurological Disease Prevalence Towards Identifying and Treat Brain Tumours.

Abstract

There are currently over 600 types of mental disorders that cause several deaths each year. Machine learning techniques can now predict the exact nature of a disorder and its severity. The use of machine learning techniques has increased the rationality of the prediction. One of the most prominent applications of this technology is in the detection of brain tumors. In this paper, we present a variety of methods that are designed to perform brain tumor analyses using machine learning. The objective of this paper is to review the literature on the subject and provide a comprehensive analysis of the various applications and achievements of machine learning in the diagnosis and treatment of neurological disorders. One of the most common methods of diagnosing brain tumors is through the use of magnetic resonance imaging.