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Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 42-565
Full Name: K. Rajeswari
Position: Assistant Professor
Age: ON
Sex: Female
Address: Department of Computer Engineering, Pimpri Chinchwad College of Engineering
Country: INDIA
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E-mail address: krajeswariphd@gmail.com
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Title of the Paper: Heart Disease Diagnosis: An Efficient Decision Support System Based on Fuzzy Logic and Genetic Algorithm
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Number of paper pages: 11
Abstract: Computerized clinical guidelines can provide significant benefits to health outcomes and costs; however, their effective implementation presents significant problems. Vagueness and ambiguity inherent in natural (textual) clinical guidelines is not readily amenable to formulating automated alerts or advice. Till date, there has not been many globally accepted clinical decision tool that achieves optimal trade-off between handling data ambiguity and good decision making. One effective solution to achieve the same would be to integrate Data Mining and Artificial Intelligence (AI) techniques. In this article, we devise an efficient clinical decision support system (CDSS) for heart disease diagnosis using Data Mining and Artificial Intelligence (AI) techniques. Apriori, an association pattern mining algorithm and Genetic Algorithm (GA) are being made use of in the proposed CDSS to formalize the treatment of vagueness in decision support architecture. The GA produces the!
set of high impact parameters and their respective optimal maximal values essential for effective heart disease diagnosis. The AI reasoning technique, Fuzzy Logic, is employed as the decision making tool in the proposed CDSS. The optimal maximal values determined using GA is used in defining the fuzzy numbers and fuzzy rules that can be expressed in linguistic variables. Lastly, based on the fuzzy membership function, the system effectively diagnoses the clinical cases of heart disease. The experimental results demonstrate the effectiveness of the proposed CDSS in heart disease diagnosis.
Keywords: Data Mining, Decision Support System (DSS) Disease diagnosis, Heart disease, Apriori algorithm, Genetic Algorithm (GA), Fuzzy Logic (FL).
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