AI-devised plans may hold key to bipolar disorder treatment
Fuzzy-logic based artificial intelligence (AI) can be used to accurately predict treatment outcomes for bipolar disorder, according to a University of Cincinnati report. Researchers used "genetic fuzzy trees", the same AI which can be deployed to shoot at pilots in air-to-air combat, to predict how bipolar patients would respond to lithium treatment with 100% accuracy. In comparison, other common treatment models could only report 75% accuracy. The model also predicted post-lithium reduction in manic symptoms with 92% accuracy, potentially paving the way for more personalised medicine.
Cohen found a receptive audience in Fleck, who was working with UC’s former Center for Imaging Research. After all, who better to tackle one of medical science’s hardest problems than a rocket scientist? Cohen, an aerospace engineer, felt up to the task.

Ernest said people should not conflate the technology with its applications. The algorithm he developed is not a sentient being like the villains in the “Terminator” movie franchise but merely a tool, he said, albeit a powerful one with seemingly endless applications.

“I get emails and comments every week from would-be John Connors out there who think this will lead to the end of the world,” Ernest said.

Ernest’s company created EVE, a genetic fuzzy AI that specializes in the creation of other genetic fuzzy AIs. EVE came up with a predictive model for patient data called the LITHium Intelligent Agent or LITHIA for the bipolar study.

“This predictive model taps into the power of fuzzy logic to allow you to make a more informed decision,” Ernest said.

And unlike other types of AI, fuzzy logic can describe in simple language why it made its choices, he said.

The researchers teamed up with Dr. Caleb Adler, the UC Department of Psychiatry and Behavioral Neuroscience vice chairman of clinical research, to examine bipolar disorder, a common, recurrent and often lifelong illness. Despite the prevalence of mood disorders, their causes are poorly understood, Adler said.

“Really, it’s a black box,” Adler said. “We diagnose someone with bipolar disorder. That’s a description of their symptoms. But that doesn’t mean everyone has the same underlying causes.”

Selecting the appropriate treatment can be equally tricky.

“Over the past 15 years there has been an explosion of treatments for mania. We have more options. But we don’t know who is going to respond to what,” Adler said. “If we could predict who would respond better to treatment, you would save time and consequences.”

With appropriate care, bipolar disorder is a manageable chronic illness for patients whose lives can return to normal, he said.