A Data Mining Model to predict and analyze the events related to Coronary Heart Disease using Decision Trees with Particle Swarm Optimization for Feature Selection
作者： A. SheikAbdullah
DOI: 10.5120/8779-2736
关键词: Set (abstract data type) 、 Coronary heart disease 、 Data mining 、 Disease 、 Feature selection 、 Health informatics 、 Particle swarm optimization 、 Computer science 、 Decision tree 、 Coronary disease 、 Heart disease
摘要: Coronary Heart Disease (CHD) is a most common type of coronary disease which has no clear origin and significant basis for premature death. Data mining become an essential methodology applications in medical informatics discovering various types diseases syndromes. Mining valuable information providing systematic decision-making the diagnosis treatment from entire database progressively becomes necessary. Classification data performs important role analysis prediction. The objective this work to build model be used by physicians also associate risk factors related heart disease. been developed using PSO – C4.5 algorithm. proposed yields reduced set features feature selection algorithm along with improved prediction accuracy. Thereby can successfully predicting other metabolic
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