Applying matrix factorization in data reconstruction for heart disease patient classification

Heart disease is one of the most severe health illnesses. Developing accurate and efficient methods to diagnose heart disease is crucial in providing good heart healthcare to patients. In this paper, a data mining based technique for diagnosing heart disease is introduced, in which heart disease related patient data sets are utilized. A matrix factorization based technique for missing data reconstruction is presented. Numerical results show that recovery data sets are able to achieve reliable diagnosis or classification performance comparable to using original completed patient datasets.