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Artificial intelligence and machine learning algorithms can help diagnose schizophrenia more quickly and accurately, according to research by the University of Alberta and IBM scientists.

The research, published in May’s npj Schizophrenia, with University of Alberta postdoctoral researcher Mina Gheiratmand as the primary author, was able to predict instances of schizophrenia with 74 per cent accuracy.

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The team, working out of the IBM Alberta Centre for Advanced Studies, also discovered the ability to predict the severity of specific symptoms in schizophrenia patients — something that wasn’t possible before.

Schizophrenia doesn’t currently have medical testing that can provide an absolute diagnosis, which can cause a significant delay before a symptomatic person is properly diagnosed.

The chronic neurological disorder affects seven or eight of every 1,000 people and those with the disorder can experience hallucinations, movement disorders and cognitive impairments.

Photo by Ed Kaiser

These findings can be used to help doctors more quickly assess and begin treatment for patients, as well as measure the progression of the disorder and the effectiveness of treatment, Gheiratmand said.