Machine Learning Systems for Detecting Schizophrenia

Abstract

Schizophrenia is a neurological disorder which has drawn a lot of attention around the world. It includes symptoms such as social withdrawal, hallucinations, delusions, confused thinking leading to other major disorders including obsessive-compulsive disorder and panic disorder. Diagnosis of psychological disorders is difficult based on one's behavioral changes. It is difficult to diagnose the exact psychological disorder due to similar symptom exhibition. More the time is taken to diagnose; more is the chance of leading to permanent disablement. In this regard, ongoing research projects are ranging from craniological studies using fMRI to retinal imaging analysis to diagnose various psychological disorders. Machine learning for image analysis in the medical domain has proven successful. This paper discusses the evolution of Schizophrenia detection technologies in relation to structural changes in brain and eye using different machine learning classification algorithms.