AI that can shoot down fighter planes helpstreat bipolar disorder12 June 2017

Retired U.S. Air Force pilot Col. Gene Lee goes upagainst 'Alpha,' a virtual opponent that uses geneticfuzzy logic, during an aerial combat simulation at Wright-Patterson Air Force Base. Credit: Lisa Ventre/UCCreative Services

The artificial intelligence that can blow humanpilots out of the sky in air-to-air combat accuratelypredicted treatment outcomes for bipolar disorder,according to a new medical study by the Universityof Cincinnati.

The findings open a world of possibility for usingAI, or machine learning, to treat disease,researchers said.

David Fleck, an associate professor at the UCCollege of Medicine, and his co-authors used artificial intelligence called "genetic fuzzy trees" topredict how bipolar patients would respond tolithium.

Bipolar disorder, depicted in the TV show"Homeland" and the Oscar-winning "Silver LiningsPlaybook," affects as many as six million adults inthe United States or 4 percent of the adultpopulation in a given year.

"In psychiatry, treatment of bipolar disorder is asmuch an art as a science," Fleck said. "Patients arefluctuating between periods of mania anddepression. Treatments will change during thoseperiods. It's really difficult to treat themappropriately during stages of the illness."

The study authors found that even the best of eightcommon models used in treating bipolar disorderpredicted who would respond to lithium treatmentwith 75 percent accuracy. By comparison, themodel UC researchers developed using AIpredicted how patients would respond to lithium100 percent of the time. Even more impressively,the UC model predicted the actual reduction inmanic symptoms after lithium treatment with 92percent accuracy.

The study authors found that even the best of theeight most common treatments was only effectivehalf the time. But the model UC researchersdeveloped using AI predicted how patients wouldrespond to lithium treatment with 88 percentaccuracy and 80 percent accuracy in validation.

It turns out that the same kind of artificialintelligence that outmaneuvered Air Force pilotslast year in simulation after simulation at Wright-Patterson Air Force Base is equally adept atmaking beneficial decisions that can help doctorstreat disease. The findings were published thismonth in the journal Bipolar Disorders.

"What this shows is that an effort funded foraerospace is a game-changer for the field ofmedicine. And that is awesome," said Kelly Cohen,a professor in UC's College of Engineering andApplied Science.

Cohen's doctoral graduate Nicholas Ernest isfounder of the company Psibernetix, Inc., anartificial intelligence development and consultationcompany. Psibernetix is working on applicationssuch as air-to-air combat, cybersecurity and

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predictive analytics. Ernest's fuzzy logic algorithm isable to sort vast possibilities to arrive at the bestchoices in literally the blink of an eye.

"Normally the problems our AIs solve have many,many googolplexes of possible solutions—effectivelyinfinite," study co-author Ernest said.

His team developed a genetic fuzzy logic calledAlpha capable of shooting down human pilots insimulations, even when the computer's aircraftintentionally was handicapped with a slower topspeed and less nimble flight characteristics. Thesystem's autonomous real-time decision-makingshot down retired U.S. Air Force Col. Gene Lee inevery engagement.

"It seemed to be aware of my intentions andreacting instantly to my changes in flight and mymissile deployment," Lee said last year. "It knewhow to defeat the shot I was taking. It movedinstantly between defensive and offensive actionsas needed."

The American Institute of Aeronautics andAstronautics honored Cohen and Ernest this yearfor their "advancement and application of artificialintelligence to large scale, meaningful andchallenging aerospace-related problems."

Cohen spent much of his career working with fuzzy-logic based AI in drones. He used a sabbatical fromthe engineering college to approach the UCCollege of Medicine with an idea: What if they couldapply the amazing predictive power of fuzzy logic toa particularly nettlesome medical problem?

Medicine and avionics have little in common. Buteach entails an ordered process—a vast decisiontree—to arrive at the best choices. Fuzzy logic is asystem that relies not on specific definitions butgeneralizations to compensate for uncertainty orstatistical noise. This artificial intelligence is called"genetic fuzzy" because it constantly refines itsanswer, tossing out the lesser choices in a wayanalogous to the genetic processes of Darwiniannatural selection.

Cohen compares it to teaching a child how torecognize a chair. After seeing just a few examples,

any child can identify the object people sit in as achair, regardless of its shape, size or color.

"We do not require a large statistical database tolearn. We figure things out. We do somethingsimilar to emulate that with fuzzy logic," Cohensaid.

A comparison of MRI brain scans of a bipolar patient(top) and a healthy patient (bottom.) Credit: DavidFleck/University of Cincinnati

Cohen found a receptive audience in Fleck, whowas working with UC's former Center for ImagingResearch. After all, who better to tackle one ofmedical science's hardest problems than a rocketscientist? Cohen, an aerospace engineer, felt up tothe task.

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Ernest said people should not conflate thetechnology with its applications. The algorithm hedeveloped is not a sentient being like the villains inthe "Terminator" movie franchise but merely a tool,he said, albeit a powerful one with seeminglyendless applications.

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

Ernest's company created EVE, a genetic fuzzy AIthat specializes in the creation of other geneticfuzzy AIs. EVE came up with a predictive model forpatient data called the LITHium Intelligent Agent orLITHIA for the bipolar study.

"This predictive model taps into the power of fuzzylogic to allow you to make a more informeddecision," Ernest said.

And unlike other types of AI, fuzzy logic candescribe in simple language why it made itschoices, he said.

The researchers teamed up with Dr. Caleb Adler,the UC Department of Psychiatry and BehavioralNeuroscience vice chairman of clinical research, toexamine bipolar disorder, a common, recurrent andoften lifelong illness. Despite the prevalence ofmood disorders, their causes are poorlyunderstood, Adler said.

"Really, it's a black box," Adler said. "We diagnosesomeone with bipolar disorder. That's a descriptionof their symptoms. But that doesn't mean everyonehas the same underlying causes."

Selecting the appropriate treatment can be equallytricky.

"Over the past 15 years there has been anexplosion of treatments for mania. We have moreoptions. But we don't know who is going to respondto what," Adler said. "If we could predict who wouldrespond better to treatment, you would save timeand consequences."

With appropriate care, bipolar disorder is amanageable chronic illness for patients whose lives

can return to normal, he said.

UC's new study, funded in part by a grant from theNational Institute of Mental Health, identified 20patients who were prescribed lithium for eightweeks to treat a manic episode. Fifteen of the 20patients responded well to the treatment.

The algorithm used an analysis of two types ofpatient brain scans, among other data, to predictwith 100 percent accuracy which patientsresponded well and which didn't. And the algorithmalso predicted the reductions in symptoms at eightweeks, an achievement made even moreimpressive by the fact that only objective biologicaldata were used for prediction rather than subjectiveopinions from experienced physicians.

"This is a huge first step and ultimately somethingthat will be very important to psychiatry and acrossmedicine," Adler said.

How much potential does this have to revolutionizemedicine?

"I think it's unlimited," Fleck said. "It's a good result.The best way to validate it is to get a new cohort ofindividuals and apply their data to the system."

Cohen is less reserved in his enthusiasm. He saidthe model could help personalize medicine toindividual patients like never before, making healthcare both safer and more affordable. Fewer side-effects means fewer hospital visits, less secondarymedication and better treatments.

Now the UC researchers and Psibernetix areworking on a new study applying fuzzy logic todiagnosing and treating concussions, anothercondition that has bedeviled doctors.

"The impact on society could be profound," Cohensaid.

More information: David E Fleck et al, Predictionof lithium response in first-episode mania using theLITHium Intelligent Agent (LITHIA): Pilot data andproof-of-concept, Bipolar Disorders (2017). DOI:10.1111/bdi.12507

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Provided by University of CincinnatiAPA citation: AI that can shoot down fighter planes helps treat bipolar disorder (2017, June 12) retrieved28 December 2021 from https://medicalxpress.com/news/2017-06-ai-fighter-planes-bipolar-disorder.html

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