AI and a computer game team up to help diagnose mental health disorders

According to researchers, using AI to help asses mental health disorders in granular detail could allow clinicians to develop more personalized treatment plans based on an individual's unique diagnosis.
Jeff Rowe

Mental health disorders are complex and, perhaps not surprisingly, often go undiagnosed. 

But the news out of Australia is that mental health providers may be getting new help in the form of a combination of a computer game and AI that a team of researchers has developed to help “identify behavioral patterns in subjects with depression and bipolar disorder, down to subtle individual differences in each group.”

Led by researchers from the data and digital specialist arm of Australia's national science agency, the study included 34 participants with depression, 33 with bipolar disorder, and a control group of 34 subjects.

According to a presentation delivered at a conference in Sydney, “the computer game presents individuals with two choices, and tracks their behavior as they respond. The complex data collected from the game is analyzed through artificial neural networks—brain-inspired systems intended to replicate the way that humans learn—which are able to disentangle the nuanced behavioral differences between healthy individuals, and those with depression or bipolar disorder.”

Dr. Amir Dezfouli, lead author of the research, a neuroscientist and machine learning expert at CSIRO’s Data61, the data and digital specialist arm of Australia's national science agency, said the research represented a possible step-change in the emerging field of computational psychiatry.

"Currently 69 percent of bipolar patients are initially misdiagnosed, and around one-third of these patients might remain misdiagnosed for 10 years or more," Dr. Dezfouli said. "If we can understand how the brain works, we can develop more accurate processes for diagnosis and more effective treatments for people with mental health disorders. Artificial intelligence and deep learning techniques allow us to analyze complex datasets and make accurate models of the brain processes involved in psychiatric disorders.”

According to Dr. Richard Nock, machine learning group leader at CSIRO's Data61, artificial intelligence has great potential in healthcare and other sectors, but “it must be deployed with privacy, ethics and inclusiveness at its core. We need to design systems that deliver benefits individually and collectively. The artificial neural network was specifically designed to produce interpretable results, and will augment the capabilities of clinicians and psychiatrists."

The researchers are seeking partners to help conduct further research to validate the technique for real-world use, providing decision support for clinicians.

"The strength of the computer game,” added Dr. Dezfouli, “is that unlike traditional mental health assessments, the results can directly reflect the brain processes that are affected due to the disorders, as individuals are responding to stimuli rather than direct questions about their mental state."