Dr. McManis is an Associate Professor of Pediatric Neurology at UAMS and the Director of Pediatric Neurodiagnostic Innovation at ACH. He is a clinical neuroscientist who combines his knowledge of neuroimaging and neurophysiology with statistics and programming to explore artificial intelligence (AI) methods to increase the efficiency and accuracy of neurodiagnostic imaging. Before arriving in Little Rock in 2020, he held director-level clinical positions for over 15 years, successfully building imaging programs from the ground up. Dr. McManis has led and collaborated on a number of research projects related to advanced neuroimaging and neurosurgery, including functional mapping, multi-modal imaging techniques, and machine learning.
In working with ACRI, Dr. McManis’ research program is focused on using AI in automated seizure and lesion detection. Historically, there has been limited success in these efforts, markedly due to the complexity of the problem. The approach Dr. McManis and his team are taking is to harness the recent advances in machine learning methods that allow computers to classify complex data sets and apply these for accurate seizure and lesion identification across a broad range of patients and types. The goal of the research program is to employ machine learning to provide evidence-based tools for clinicians and substantially improve patient treatment and outcomes.