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Improving Cardiovascular Disease Detection With Autoe-som Through Deep Learning and Feature Selection

Year: 2025

Type: article

Abstract: CVD is responsible for numerous deaths worldwide and impacts millions of individuals annually. Its impact spans all demographics, making it a major public health concern worldwide. In CVD, the heart does not pump sufficient blood to the rest of the body. A precise analysis of CVD is critical for its prevention and treatment. CVD encompasses four categories, including coronary heart disease, transient ischemic attack, peripheral artery disease, and aortic disease. These symptoms often manifest in the elderly and can be mistaken for other diseases, making an accurate diagnosis challenging and potentially leading to fatal outcomes.

Source: Sylwan

DOI: 10.59879/oyehy

Authors: B. Dhiyanesh, Parveen Begam Abdul Kareem, P. Shanmugaraja, V. Anusuya, A. Baseera

Institutions: SRM Institute of Science and Technology, Sona College of Technology, VIT Bhopal University

Language: English

Topic: Artificial Intelligence in Healthcare

Subfield: Health Information Management

Field: Health Professions

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: bronze

OpenAlex ID: W4409476697

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