How AI and Machine Learning are Aiding Schizophrenia Research - THINK Blog

July 21, 2017 Written by: Dr. Guillermo Cecchi In the U.S. about 20 percent of adults suffer from a mental health condition, ranging from depression to bipolar disorder to schizophrenia, and about half of those with severe psychiatric disorders receive no treatment. While early identification, diagnosis, and treatment for patients with psychosis tends to mean improved outcomes, there continues to be significant barriers in achieving this. For schizophrenia, there is no medical testing that can provide an absolute diagnosis; this can mean significant delay before a symptomatic person is successfully diagnosed. Earlier this year, IBM scientists collaborated with researchers at the University of Alberta and the IBM Alberta Centre for Advanced Studies (CAS) to publish new research regarding the use of AI and machine learning algorithms to predict instances of schizophrenia with a 74 percent accuracy. The research also shows a further capability to predict the severity of specific symptoms in schizophrenia patients – something that was not possible before.