The invention relates to the technical field of
data mining, in particular to a method for constructing a myocardial
rehabilitation decision support system based on case-based reasoning. The method comprises the following steps: collecting and fusing historical cardiomyopathology case data, and carrying out sensitive feature desensitization to obtain desensitization data; dividing myocardial
rehabilitation cases and integrating abnormal electrocardiogram waveform characteristics to obtain abnormal waveform data of the
rehabilitation cases; constructing an abnormal waveform detection model, and detecting abnormal waveforms by using the abnormal waveform detection model to obtain abnormal electrocardiogram waveform myocardial case data; performing
trend analysis on the abnormal waveform data, and calculating myocardial rehabilitation influence factors; evaluating the doctor treatment priority based on the influence factors, and constructing a treatment doctor
recommendation model; and in combination with the
recommendation model and the detection model, constructing and optimizing a myocardial rehabilitation decision-making
system so as to obtain a myocardial rehabilitation decision-making
support system. According to the invention, based on
data mining, the accuracy and effectiveness of myocardial rehabilitation research on historical cardiomyopathology cases are realized.