Diagnosis of heart disease by using a radial basis function network classification technique on patients' medical records

M. Alsalamah, Saad Amin, J. Halloran

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Abstract

Heart disease is defined as any abnormal heart condition, and it is prevalent in people today. Considering human body as one big system, many factors play role on this disease. Examining the body provides quite lot of data in many different ways, though understanding the signs in collected data about heart disease requires experience, knowledge, and time from physicians. Computer based expert systems are designed to reduce the burden on physicians by automation. One of the important components of expert systems is data classifiers, and in this paper, I present the use of Radial Basis Function Networks (RBFN) with a Gaussian function as data classifier for heart disease classification. The proposed method in the paper makes use of same training data after they are used for training to reduce false classifications which makes this project unique in itself. For development and testing, I utilized patient records from Prince Sultan Cardiac Center-Qassim in Saudi Arabia. This paper discusses the use of RBFN for the classification of heart diseases, and it proposes a model system that forms data collection, processing, storage, and usage procedures.
Original languageEnglish
Title of host publicationConference Proceedings - 2014 IEEE MTT-S International Microwave Workshop Series on: RF and Wireless Technologies for Biomedical and Healthcare Applications, IMWS-Bio 2014
PublisherIEEE
VolumeArticle number 7032401
ISBN (Print)978-147995447-6
DOIs
Publication statusPublished - 2014
Event2014 IEEE MTT-S International Microwave Workshop Series on RF and Wireless Technologies for Biomedical and Healthcare Applications - London, United Kingdom
Duration: 8 Dec 201410 Dec 2014

Workshop

Workshop2014 IEEE MTT-S International Microwave Workshop Series on RF and Wireless Technologies for Biomedical and Healthcare Applications
Abbreviated titleIMWS-Bio 2014
CountryUnited Kingdom
CityLondon
Period8/12/1410/12/14

Bibliographical note

This paper is not available on the repository. This paper was give at the 2014 IEEE MTT-S International Microwave Workshop Series on RF and Wireless Technologies for Biomedical and Healthcare Applications, IMWS-Bio 2014; Canary Wharf London; United Kingdom; 8 December 2014 through 10 December 2014

Keywords

  • Artificial intelligence
  • data classification
  • heart diseases
  • Radial Basis Function Networks

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  • Cite this

    Alsalamah, M., Amin, S., & Halloran, J. (2014). Diagnosis of heart disease by using a radial basis function network classification technique on patients' medical records. In Conference Proceedings - 2014 IEEE MTT-S International Microwave Workshop Series on: RF and Wireless Technologies for Biomedical and Healthcare Applications, IMWS-Bio 2014 (Vol. Article number 7032401). IEEE. https://doi.org/10.1109/IMWS-BIO.2014.7032401