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Mount Sinai makes a step forward in using machine learning to interpret medical images 

Researchers at Mount Sinai are using machine learning algorithms to diagnose young athletes with HCM, a disease in which the a portion of the heart muscle gets enlarged for no clear reason. It’s the leading cause of sudden death in youth athletes.  More specifically, the algorithm interprets echocardiographic images to better distinguish between HCM and other … Continue reading “Mount Sinai makes a step forward in using machine learning to interpret medical images “

Researchers at Mount Sinai are using machine learning algorithms to diagnose young athletes with HCM, a disease in which the a portion of the heart muscle gets enlarged for no clear reason. It’s the leading cause of sudden death in youth athletes. 

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More specifically, the algorithm interprets echocardiographic images to better distinguish between HCM and other physiological changes that cause the heart to appear large. Today, a highly trained cardiologist would need to weigh in. 

“Our approach shows a promising trend in using automated algorithms as precision medicine techniques to augment physician-guided diagnosis,” said study author Joel Dudley, in a statement. The results were published online here. 

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About the author

Christina Farr is a San Francisco-based journalist specializing in health and technology. Before joining Fast Company, Christina worked as a reporter for VentureBeat, Reuters and KQED

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