Publication Type : Conference Paper
Thematic Areas : Medical Sciences, Biotech
Publisher : TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region
Source : TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region (2003)
Campus : Coimbatore
School : School of Engineering
Center : Biotechnology, Computational Engineering and Networking, Electronics Communication and Instrumentation Forum (ECIF)
Department : Electronics and Communication, biotechnology
Year : 2003
Abstract : Ischemic heart disease (IHD) is one of the toughest challenges to doctors in-making right decisions due to its skimpy symptoms and complexity. We have analyzed IHD data from 65 patients to provide an aid for decision-making. Decision trees give potent structural information about the data and thereby serve as a powerful data mining tool. Support vector machines serve as excellent classifiers and predictors and can do so with high accuracy. Our tree based classifier uses non-linear proximal support vector machines (PSVM). The accuracy is very high (100% for training data) and the tree is small and precise.
Cite this Research Publication : Dr. Soman K. P., Shyam, D. M., and Madhavdas, P., “Efficient Classification and Analysis of Ischemic Heart Disease using Proximal Support Vector Machines based Decision Trees”, in TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region, 2003.