Communications of the ACM
Mania and the Machine
University of Cincinnati researchers conducting a study on using artificial intelligence to anticipate the outcomes of bipolar disorder therapies found "genetic fuzzy trees" generated an accurate predictive model of patient response to lithium.
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Researchers at the University of Cincinnati (UC) have conducted a study on using artificial intelligence (AI) developed for aerospace simulation to anticipate the outcomes of bipolar disorder therapies.
The team used "genetic fuzzy trees" to generate a 100% accurate predictive model of patient response to lithium, while even the best common models were only 75-percent accurate in comparison.
The genetic fuzzy AI continuously refines its answer to problems, rejecting lesser choices in a manner similar to Darwinian natural selection.
AI developer Psibernetix produced a genetic fuzzy AI to specifically generate AIs of its type, and it created the LITHium Intelligent Agent for the UC study. The algorithm used brain-scan analysis to predict patients' positive and negative responses to lithium, as well as reductions of symptoms at eight weeks of treatment.
"This is a huge first step and ultimately something that will be very important to psychiatry and across medicine," says UC's Caleb Adler.
From UC Magazine
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