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Evaluating the Clinical Domain with Data Mining Using Classification and Regression Tree (cart) & Particle Swarm Optimization (Pso) Method
Disease management programs, which use no advanced information and computer technology, are as effective as telemedicine but more efficient because less costly. We proposed a platform to enhance effectiveness and efficiency of home monitoring using data mining for early detection of any worsening in patient's condition. These worsening could require more complex and expensive care if not recognized. The paper is to describe the remote health monitoring platform which is designed and realized that supports heart failure severity assessment offering functions of data mining based on CART and PSO method. In this paper, existing method (CART) is applied to detect heart failure which takes more time and more memory to produce the result. Proposed PSO method takes less time and less memory compare to CART. Thus PSO is best suitable to detect heart failure.
Keywords
Particle Swarm Optimization (PSO), Classification and Regression Tree
(CART), Data Mining (DM), Heart Failure (HF), Heart Rate Variability (HRV), Home
Monitoring (HM)
(CART), Data Mining (DM), Heart Failure (HF), Heart Rate Variability (HRV), Home
Monitoring (HM)
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