Programs
- M. Tech. in Automotive Engineering -Postgraduate
- Paediatric Point of Care Ultrasound & Critical Care Certificate Course -Fellowship
Publication Type : Conference Proceedings
Publisher : IEEE Tencon
Source : Published by IEEE Press as Proceedings of IEEE Tencon Conference on Convergent Technologies for Asia-Pacific Region 2003, held at Bangalore, India on Oct 15-17, 2003.
Url : https://www.frontiersin.org/10.3389%2Fconf.fncel.2017.37.00006/event_abstract
ISBN : 0-7803-8162-9
Campus : Amritapuri
School : School of Biotechnology
Center : Amrita Mind Brain Center
Department : 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 : S. Diwakar, Mohandas P., Soman K.P., Efficient classification and analysis of Ischemic Heart Disease using Proximal Support Vector Machines based Decision Trees published by IEEE press as proceedings of IEEE Tencon 2003, held at Bangalore, India on Oct 15-17, 2003.