The approach, a “deep learning” technology that incorporates neural networks and survival analysis and looks at raw cardiac images, outperformed standard statistical-based survival models in patients with ischemic heart disease, according to the April 7 study in Nature Cardiovascular Research.
“This technology has the potential to transform clinical decision-making by offering accurate and generalizable predictions of patient-specific survival probabilities of arrhythmic death over time,” the authors wrote.
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