Method and System for Predicting Recurrence Risk of Myocardial Infarction in Cardiac Rehabilitation Patients by using Clinical data, Lifelog data, and Machine Learning Algorithm

摘要

Disclosed is a method and system for predicting the risk of recurrence of myocardial infarction in cardiac rehabilitation patients using machine learning techniques. According to an aspect of the present embodiment, in a computer-implemented method for predicting the risk of recurrence of myocardial infarction in a cardiac rehabilitation patient, an electronic medical record (EMR) of a cardiac rehabilitation patient and of the cardiac rehabilitation patient measured during cardiac rehabilitation Obtaining lifelog data; Generating a data set to be input into a machine learning-based risk prediction model by extracting preset features from the electronic medical record and the life log data; Determining whether the cardiac rehabilitation patient is at risk of recurrence of myocardial infarction or an index of risk of recurrence of myocardial infarction using the machine learning-based risk prediction model; And providing a step of providing a determined risk of recurrence of myocardial infarction or a risk index of recurrence of myocardial infarction.