Sanjiv M. Narayan, MD, PhD, and professor of cardiovascular medicine at Stanford University in California, concentrates his research on the use of bioengineering techniques to treat cardiac arrhythmias at the Computational Arrhythmia Research Laboratory. A former professor of medicine at UC San Diego, Sanjiv Narayan is co-director of the Stanford Arrhythmia Center.
Stanford’s long-time reputation as a focus for next-generation computational and artificial intelligence work applied to medicine continues. Stanford university’s recent work in this field includes using artificial intelligence to detect arrhythmias by members of the Stanford Machine Learning Group. The group created a deep learning algorithm that has shown greater success in identifying arrhythmias than a control group consisting of human cardiologists. The algorithm is able to diagnose more than a dozen subsets among heart rhythm disorders. In addition, it can work with data from more remote communities in which many residents lack access to cardiologists.
The model developed by the Machine Learning Group, in collaboration with the company iRhythm Technologies, diagnoses rhythm disorders based on single-lead electrocardiogram signals.
According to researchers, the particular excitement inherent in this project lies in the algorithm’s ability to provide speed and accuracy of diagnosis across so many arrhythmia types, an accomplishment that had not previously been possible.