Cardiovascular Disease Prediction Using Deep Learning Algorithm

Registration ID: IJNRD_220309

Published ID: IJNRD2405037

DOI: Click Here to Get

M.SATHYA SUNDARAM , AJAY.S , DHARANI DHARAN.N , JEYAPANDI.M

Cardiovascular disease, Deep learning, Convolutional neural networks, Recurrent neural networks, Disease prediction, Healthcare, Medical diagnosis

Cardiovascular disease (CVD) remains a major global health problem, causing the majority of deaths and illnesses worldwide. Early detection and prediction of CVD is essential for effective prevention and management strategies. In recent years, deep learning algorithms have shown great results in many medical applications, including disease prediction. This article presents an in-depth study of predicting cardiovascular disease using clinical data and demographic characteristics. We use state-of-the-art deep learning architectures, including convolutional neural networks (CNN) and recurrent neural networks (RNN), to extract meaningful patterns and relationships from data input. The proposed model is trained from a large dataset containing different patient populations, medical histories, and measurements. Experimental results demonstrate the effectiveness of deep learning models in predicting cardiovascular diseases. We also compare the performance of the model with traditional machine learning methods and demonstrate the advantages of deep learning methods in CVD prediction. This research contributes to the development of powerful and accurate tools for early detection and risk stratification of cardiovascular diseases, ultimately supporting timely intervention and personalized treatment.

Published Paper   E-Certificate

M.SATHYA SUNDARAM , AJAY.S, DHARANI DHARAN.N, & JEYAPANDI.M (May-2024). Cardiovascular Disease Prediction Using Deep Learning Algorithm. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(5), a352-a359. https://ijnrd.org/papers/IJNRD2405037.pdf

Volume 9 Issue 5, May-2024

Pages : a352-a359

Paper Reg. ID: IJNRD_220309

Published Paper Id: IJNRD2405037

Downloads: 000121989

Research Area: Engineering

Country: NAMAKKAL, TAMIL NADU, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2405037.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405037

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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