Coronary heart disease patient models based on inductive machine learning

Abstract

The work presents a model construction process which is a combination of the inductive learning based detection of interesting sub- groups, comparative statistical analyses of risk factors for these groups, and expert knowledge interpretation of the results. The induced models describe population subgroups with unproportionately high rate of the disease what might be helpful in the prevention process.