A paper by Rishi Kamaleswaran, PhD, about the use of artificial intelligence (AI) to classify cardiac arrhythmia made the 2018 highlights section of the scientific journal, Psychological Measurement. Dr. Kamaleswaran is an assistant professor in the Department of Pediatrics in the College of Medicine at the University of Tennessee Health Science Center (UTHSC).
“I developed this classifying system as part of a competition, called the PhysioNet Computing in Cardiology 2017 Challenge,” Dr. Kamaleswaran said. “It received the top ranking in the competition, and suggests that this system could be successfully used on humans. However, much more work needs to be done to get to that point.”
Highlight articles for the journal were chosen based on high quality reviewer reports, impressive usage statistics and citations, and personal recommendation by the Psychological Management editorial board.
Dr. Kamaleswaran’s research focuses on applying artificial intelligence in medicine, specifically on point-of-care analytics that involve real-time data streams, from patient monitors in the ICU or wearables that produce signals, such as electrocardiograms, respiratory waveform, photoplethysmography, blood pressures etc. His goal is to integrate all these real-time signals to forecast any potential clinical deterioration in areas such as transplant, critical care, cardiology, sickle cell disease, and Parkinson’s disease.