Coronary atherosclerotic heart disease diagnosis recommendation method

The invention discloses a coronary atherosclerotic heart disease diagnosis recommendation method. The method comprises the following steps: step 1, case data mining; step 2, information structured extraction; step 3, data set processing; step 4, data exploratory analysis; 5, automatically screening variables; step 6, machine learning modeling; step 7, evaluating a modeling process; 8, deploying the model; according to the coronary atherosclerotic heart disease diagnosis method, the cases of the patient are taken as the training data set to be substituted into the machine learning model for iterative learning to form the coronary atherosclerotic heart disease diagnosis model, so that the disease of the patient is diagnosed and recommended by using the model, the misdiagnosis condition caused by manual diagnosis is avoided, and the diagnosis efficiency of the coronary atherosclerotic heart disease is improved. Meanwhile, automatic judgment is carried out in the diagnosis process according to rules of clinical g