Detecting heart ailments by investigating ECG with neural networks
by B. Prabadevi; N. Deepa; L.B. Krithika; Ravi Raj Gulati; R. Sivakumar
International Journal of Medical Engineering and Informatics (IJMEI), Vol. 14, No. 5, 2022

Abstract: Heart ailments or cardiovascular diseases (CVD) are the diseases that incorporate the blood vessels or heart, which is common among various age groups. Though numerous techniques have been used to classify heart abnormalities, such as classification and regression trees (CART), they are less accurate. Therefore, a technique for early detection of heart ailments with more accuracy is mandatory. A model has been designed and proposed to detect the heart ailments using three-layered neural networks for better accuracy. Electrocardiogram (ECG or EKG) is used to identify arrhythmia (irregular heartbeat) accurately, and the UC Irvine (UCI) arrhythmia dataset of ECG reports are used to implement a classification for different types of heart abnormalities.

Online publication date: Wed, 07-Sep-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Medical Engineering and Informatics (IJMEI):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com