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  Authors

Bommaiah Boya,Dr.P.Devaraju

  Keywords

Cardiovascular diseases (CVDs), Electrocardiograms (ECG), Echocardiography, angiography, Machine Learning, Deep Learning.

  Abstract


Cardiovascular diseases (CVDs) are the foremost cause of death worldwide, covering conditions such as coronary artery disease, arrhythmias, heart failure, congenital defects, and stroke. Their development is influenced by risk factors including hypertension, diabetes, obesity, smoking, high cholesterol, sedentary lifestyle, and genetics. Traditional diagnostic tools like ECG, echocardiography, angiography, and stress testing remain common but are often costly, labor-intensive, and may not detect disease at early stages. Advances in artificial intelligence have introduced machine learning and deep learning methods as efficient alternatives for disease prediction. These models are capable of handling diverse datasets, ranging from clinical records to medical images, and can identify patterns that aid in accurate and timely diagnosis. This paper reviews CVD types, major risk factors, diagnostic methods, and previously applied ML and DL approaches, highlighting their strengths, limitations, and challenges such as data imbalance, lack of interpretability, and limited generalizability. Future research directions emphasize multi-modal data fusion, explainable AI frameworks, and improved neural network designs to build robust and clinically reliable diagnostic tools for cardiovascular diseases.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2309759

  Paper ID - 295787

  Author type - Indian Author

  Page Number(s) - g262-g269

  Pubished in - Volume 11 | Issue 9 | September 2023

  DOI (Digital Object Identifier) -   

  No Of Downloads - 98

  Author Country - India, -, -, -, -, Science and Technology

  Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Published Paper PDF : - http://www.ijcrt.org/papers/IJCRT2309759

  Published Paper URL: : - http://ijcrt.org/viewfull.php?&p_id=IJCRT2309759

  Published Paper PDF Downlaod: - download.php?file=IJCRT2309759

  Cite this article

Bommaiah Boya,Dr.P.Devaraju,   "A Review On Machine Learning And Deep Learning Approaches For Cardiovascular Disease Prediction: Risk Factors, Diagnostic Approaches, Models, And Future Challenges", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 9, pp.g262-g269, September 2023, Available at :http://www.ijcrt.org/papers/IJCRT2309759.pdf

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