NDLI: Implementing Decision Tree Fuzzy Rules in Clinical Decision Support System after Comparing with Fuzzy Based and Neural Network Based Systems

Content Provider	IEEE Xplore Digital Library
Author	Anooj, P.K.
Copyright Year	2013
Description	Author affiliation: Dept. of Inf. Technol., Al Musanna Coll. of Technol., Al Musanna, Oman (Anooj, P.K.)
Abstract	As people have interests in their health recently, development of medical domain application has been one of the most active research areas. One example of medical domain application is detection system for heart disease based on computer-aided diagnosis methods, were the data are obtained from some other sources and are evaluated based on computer based applications. At the earlier time, the use of computer is to build knowledge based clinical decision support system which uses knowledge from medical experts and transfers this knowledge into computer algorithms manually. This process is time consuming and really depends on medical expert's opinion which may be subjective. To handle this problem, machine learning techniques have been developed to gain knowledge automatically from examples or raw data. Here, a weighted fuzzy rule-based clinical decision support system (CDSS) is presented for the diagnosis of heart disease, automatically obtaining the knowledge from the patient's clinical data. The proposed clinical decision support system for risk prediction of heart patients consists of two phases, (1) automated approach for generation of weighted fuzzy rules, and (2) developing a fuzzy rule-based decision support system. In the first phase, we have used the mining technique, attribute selection and attribute weightage method to obtain the weighted fuzzy rules. Then, the fuzzy system is constructed in accordance with the weighted fuzzy rules and chosen attributes. Finally, the experimentation is carried out on the proposed system using the datasets obtained from the UCI repository and the performance of the system is compared with the neural network-based system utilizing accuracy, sensitivity and specificity.
Starting Page	1
Ending Page	6
File Size	345739
Page Count	6
File Format	PDF
ISBN	9781479928453
DOI	10.1109/ICITCS.2013.6717845
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Heart Decision support systems Accuracy Databases Vectors Data mining Diseases
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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