Machine Learning for Arrhythmia Detection
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December 20, 2017
Dr. Gari Clifford, DPhil has been studying artificial intelligence (AI) and its utility in healthcare for two decades. He holds several prestigious positions in academia and is an Associate Professor of Biomedical Informatics at Emory University and an Associate Professor of Biomedical Engineering at Georgia Institute of Technology. We met him at the San Francisco Data Institute Conference in October where he chaired sessions on Machine Learning and Health. Gari recently held a competition challenging data scientists to develop predictive algorithms for the early detection of Atrial Fibrillation, using mobile ECG machines. He shares insight into the complexity of using AI to diagnose health conditions and offers a glimpse into the future of healthcare and medical information. Here’s the outline of this interview with Gari Clifford: [00:01:07] The road to machine learning and mobile health. [00:01:27] Lionel Tarassenko: neural networks and artificial intelligence. [00:03:36] San Francisco Data Institute…