A smart healthcare monitoring method and system for heart disease prediction based on ensemble deep learning and shape fusion are presented. The smart healthcare monitoring method for heart disease prediction based on ensemble deep learning and shape fusion proposed in the present invention includes the steps of collecting data on heart disease patients through wearable sensor measurement and electronic medical testing, and FRF (Framingham Risk Functions) with EMR (Framingham Risk Functions) Electronic Medical Record), combining data collected through FRF and wearable sensor measurements using a shape fusion approach to generate medical data on heart disease, selecting shapes based on information acquisition techniques, and conditionally Calculating shape weights based on probability and training to predict heart disease of a patient through an ensemble deep learning classifier using shape weights based on a shape selected based on an information acquisition technique and a conditional probability.
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