Research Area:  Machine Learning
Early detection of heart disease is an important challenge since 17.3 million people yearly lose their lives due to heart diseases. Besides, any error in diagnosis of cardiac disease can be dangerous and risks an individual life. Accurate diagnosis is therefore critical in cardiology. Data Mining (DM) classification techniques have been used to diagnosis heart diseases but still limited by some challenges of data quality such as inconsistencies, noise, missing data, outliers, high dimensionality and imbalanced data. Data preprocessing (DP) techniques were therefore used to prepare data with the goal of improving the performance of heart disease DM based prediction systems.
Author(s) Name:  H.Benhar, A.Idri, and J.L.Fernández-Alemán
Journal name:  Computer Methods and Programs in Biomedicine
Publisher name:  Elsevier B.V.
Volume Information:  Volume 195, 105635
Paper Link:   https://www.sciencedirect.com/science/article/abs/pii/S0169260720314681