SYDNEY, Sept. 27 (Xinhua) -- Machine learning, also known as artificial intelligence, could be a useful tool for predicting how well people at high risk of psychosis or suffering from depression will function socially in the future, according to latest Australian-led research.
Using clinical, neuroimaging-based and machine-learning methods to analyze the results of brain imaging and clinical measures from client interviews, the researchers found that artificial intelligence outperformed human experts and could correctly predict social outcomes one year later in up to 83 percent of patients in clinical high-risk states for psychosis and 70 percent of patients with recent-onset depression, they said in a statement on Thursday. Social outcomes include the ability to carry out social interactions or create and maintain relationships with others.
"Predicting social outcomes is important as among young people and emerging adults in OECD countries the top causes of disability' and poor social functioning is included in that are mostly disorders of mental health, including those that typically present with a first episode of psychosis," said Professor Stephen Wood from the Orygen National Centre of Excellence in Youth Mental Health research organization.
"By being able to better predict what will happen to people at high risk of psychosis or with recent onset depression over time, we are able to provide individualized treatments to clients when they first present to mental health services and potentially improve their social functioning."
The researchers tracked 116 people at clinical high-risk of developing psychosis and 120 people experiencing recent onset depression aged 15 to 40, as well as 176 healthy control participants. Their findings were published in medical journal JAMA Psychiatry.
