John Pestian

Dr. Pestian's research focuses on developing advanced technology for the care of neuropsychiatric illness. Using artificial intelligence, his team integrates analyses of trait and state characteristics for early identification of both neurological and psychiatric illness. His lab developed and implemented an automated, electronic health record surveillance system that processes clinician notes to identify epilepsy surgery candidates up to two years earlier than traditional approaches. The lab also focuses on earlier identification of individuals at risk of suicide, depression, and bipolar and anxiety disorders using verbal and nonverbal language. His current projects include fusion of linguistic, acoustic, and visual cues that are being tested in selected Cincinnati Public Schools and Cincinnati Children’s clinics. Dr. Pestian and his lab have 18 issued patents and he is active in the entrepreneurial community. This activity has yielded over 500 jobs and one-half billion in revenue have been created. One invention, Processing Text With Domain- Specific Spreading Activation Methods, is a platform for neuropsychiatric research. Another, Optimization and Individualization of Medication Selection and Dosing, has been used for optimal mental health drug selection on more than 420,000 people. He and his colleagues have published more than 80 peer reviewed publications that focus on applied and translational sciences apropos to artificial intelligence.

Associated articles

JTEHM, Articles, Published Articles
Improving Detection of Rapid Cystic Fibrosis Disease Progression—Early Translation of a Predictive Algorithm into a Point-of-Care Tool
      Early Access Note: Early Access articles are new content made available in advance of the final electronic or print versions and result from IEEE’s Preprint or Rapid Post processes. Preprint articles are peer-reviewed but not fully edited. Rapid Post articles are... Read more
JTEHM, Articles, Published Articles
Improving Detection of Rapid Cystic Fibrosis Disease Progression—Early Translation of a Predictive Algorithm into a Point-of-Care Tool
      Abstract The clinical course of cystic fibrosis (CF) lung disease is marked by acute drops of lung function, defined clinically as rapid decline. As such, lung function is monitored routinely through pulmonary function testing, producing hundreds of measurements over the lifespan... Read more