U of A research shows faster, more accurate schizophrenia diagnosis possible with artificial …

Mina Gheiratmand and Russell Greiner use artificial intelligence to predict instances of schizophrenia. (University of Alberta) A partnership between University of Alberta researchers at the Alberta Machine Intelligence Institute (Amii) and IBM scientists has broken new ground in the use of artificial intelligence to predict cases of schizophrenia. In a recently published study, the researchers demonstrate that machine learning algorithms can predict instances of schizophrenia with 74 per cent accuracy, a number comparable to what human doctors are currently doing. The researchers were also able to predict the severity of specific symptoms in schizophrenia patients — something that wasn’t possible before.  By using artificial intelligence and machine learning, “computational psychiatry” can be used to help clinicians more quickly assess and treat patients with schizophrenia. “This was a very fruitful collaboration between the U of A and IBM, ” said postdoctoral fellow Mina Gheiratmand, who co-authored the research. Brain imaging captured using functional magnetic resonance imaging. (University of Alberta) “What we did basically was to use machine learning techniques for predicting the instances of schizophrenia — so who basically has schizophrenia — and this was a little challenging.” Currently, doctors are limited to diagnosing patients while relying on behavioural symptoms, and there is no medical testing that can provide an absolute diagnosis. That can mean significant delays before a…


Link to Full Article: U of A research shows faster, more accurate schizophrenia diagnosis possible with artificial …

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