AI ‘learns’ to predict schizophrenia from brain MRI
A collaborative effort between IBM and the University of Alberta in Canada has produced artificial intelligence (AI) and machine learning algorithms were able to examine MRI and predict schizophrenia with 74 percent accuracy.
The retrospective analysis, published July 21 in Schizophrenia, also showed the technology was able to determine the severity of symptoms by examining activity in various regions of the brain.
The team examined brain MRI of 95 participants, using the images to develop a machine-learned model of schizophrenia. The AI was then able to distinguish between those with schizophrenia and a control group.
“The ultimate goal of this research effort is to identify and develop objective, data-driven measures for characterizing mental states, and apply them to psychiatric and neurological disorders” said Ajay Royyuru, vice president of healthcare and life sciences with IBM Research. “We also hope to offer new insights into how AI and machine learning can be used to analyze psychiatric and neurological disorders to aid psychiatrists in their assessment and treatment of patients.”
The full study is available for free at Schizophrenia.
Nicholas joined TriMed in 2016 as the managing editor of the Chicago office. After receiving his master’s from Roosevelt University, he worked in various writing/editing roles for magazines ranging in topic from billiards to metallurgy. Currently on Chicago’s north side, Nicholas keeps busy by running, reading and talking to his two cats.