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This research prospectively evaluated a machine learning algorithm that identifies candidates for neurologic surgery to control epilepsy.
This project looked at the ability of EHRs to facilitate patient outcomes tracking, improve provider communication, reduce medical errors, and improve quality of care.
This project evaluated the Pharmaceutical Safety Tracking (PhaST) system, which monitors medication safety in children and adolescents who are taking antidepressants.
Developed, implemented, and evaluated a cooperative effort for using health IT to facilitate a continuum of appropriate medical and developmental care, from the time infants are admitted to Neonatal Intensive Care Units (NICUs), through the transition process to community-based health care services for infants most at-risk for long-term neurodevelopmental problems.