Heart disease diagnosis using C4.5 algorithms: A case study

Data mining (DM) is a powerful process to extract knowledge and discover new patterns embedded in large data sets. DM has been increasingly used in medicine, particularly in cardiology. In fact, data mining applications can greatly benefits all parts involved in cardiology such as patients, cardiologists and nurses. Among the various units of a cardiology department, Autonomic Nervous System (ANS) is one of the most important and active unit. Thus, the aim of this study is to build a decision tree-based classifier using a data set collected from an ANS unit of the Moroccan university hospital Avicenne. The decision tree construction algorithm used in this study is C4.5. The classifier obtained presented a high level of accuracy measured in terms of error rate.