An Expert System Working Upon an Ensemble PSO-Based Approach for Diagnosis of Coronary Artery Disease
Publish place: 18th Iranian conference on Biomedical Engineering
Publish Year: 1390
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICBME18_094
تاریخ نمایه سازی: 27 فروردین 1393
Abstract:
It is evident that usage of data mining methods in disease diagnosis has been increasing gradually. In this paper,diagnosis of Coronary Artery Disease, which is one of the most well-known diseases that cause heart failure, was conducted with such a data mining system. Many researchers have attempted to develop a medical expert system to increase the ability of physicians in detecting this disease. This paper proposes a new ensemble PSO-based approach to extract a set of rules for diagnosis of coronary artery disease. The new presented boosting mechanism considers the cooperation between generated fuzzy if-then rules using the PSO metaheuristic. We have evaluated our new classification approach using the well-known Cleveland data set. Results indicate that the proposed learning method can detect the coronary artery disease with an acceptable accuracy. In addition, the extractedfuzzy rules have significant interpretability either.
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Authors
Najmeh Ghadiri Hedeshi
Faculty of Electrical and Computer Engineering, Tarbiat Modares University
Mohammad Saniee Abadeh
Assistant Professor, Faculty of Electrical and Computer Engineering, Tarbiat Modares University
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