EconPapers    
Economics at your fingertips  
 

An effective healthcare monitoring system in an IoMT environment for heart disease detection using the HANN model

Karuppuchamy V. and Palanivel Rajan S.

Computer Methods in Biomechanics and Biomedical Engineering, 2024, vol. 27, issue 1, 67-76

Abstract: The proposed work aims to develop an automated machine learning based network model for heart disease prediction with better accuracy. In the pre-processed data, the most significant features are selected using the White Shark Optimization based Linear Discriminant Analysis (WSO-LDA) technique, reducing computational complexity. Finally, the selected features are fed to the Hybrid Artificial Neural Network (HANN) with a Multi-Objective Spotted Hyena optimization (MOSHO) based classification stage. This stage classifies heart disease with minimized processing time.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10255842.2023.2245521 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:gcmbxx:v:27:y:2024:i:1:p:67-76

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/gcmb20

DOI: 10.1080/10255842.2023.2245521

Access Statistics for this article

Computer Methods in Biomechanics and Biomedical Engineering is currently edited by Director of Biomaterials John Middleton

More articles in Computer Methods in Biomechanics and Biomedical Engineering from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:gcmbxx:v:27:y:2024:i:1:p:67-76