
	Trends in Applied Sciences Research
	Year: 2009 \| Volume: 4 \| Issue: 1 \| Page No.: 36-46

Artificial Neural Network as a Clinical Decision-Supporting Tool to Predict Cardiovascular Disease

Beatrice Fidele, Jayrani Cheeneebash, Ashvin Gopaul and Smita S.D. Goorah

Abstract: The aim of the study is to use artificial intelligence tools as a clinical decision support in assessing cardiovascular risk in patients. A two-layer neural network using the Levenberg-Marquardt algorithm and the resilient backpropagation have been used in the proposed artificial neural network. It has been shown how this network is efficient in predicting cardiovascular risk in individual patients by using the Long Beach dataset. The use of this new network seems to better address the prediction of cardiovascular disease at an individual level.

PDF Fulltext XML References Citation Report Citation

RELATED ARTICLES:

•	A Critical Review for an Accurate and Dynamic Prediction for the Outcomes of Traumatic Brain Injury based on Glasgow Outcome Scale

•	Effect of Leaky Rate on the Stability of Autonomously Echo State Network

•	VHDL Modeling of EMG Signal Classification using Artificial Neural Network

How to cite this article:

Beatrice Fidele, Jayrani Cheeneebash, Ashvin Gopaul and Smita S.D. Goorah, 2009. Artificial Neural Network as a Clinical Decision-Supporting Tool to Predict Cardiovascular Disease. Trends in Applied Sciences Research, 4: 36-46.

URL: https://scialert.net/abstract/?doi=tasr.2009.36.46

COMMENT ON THIS PAPER

Navigation


		Previous Issues
		Submit a Manuscript

Science Alert