TY  - GEN
AU  - Zoya Farheen 
AU  - Saniya Fathima
TI  - Cardiovascular disease detection using artificial intelligence and machine learning 
PY  - 2024///
CY  - Ghaziabad
PB  - MAT Journals
KW  - Data Science
N2  - Artificial Intelligence (AI) is playing an increasingly important role in healthcare, particularly in diagnosing and treating Cardiovascular Diseases (CVD), such as heart failure, atrial fibrillation, and coronary artery disease. This study employs advanced AI techniques, including Convolutional Neural Networks (CNNs) and machine learning models, to analyze Electrocardiograms (ECGs) and medical imaging data for early detection of CVD. The methodology involves pre-processing medical data, feature extraction, and model training to identify subtle patterns indicative of cardiovascular conditions. The results demonstrate significant success, with the model achieving an accuracy rate exceeding 85%, effectively identifying early-stage CVD cases and providing timely diagnostic support. These findings highlight the potential of AI to improve diagnostic accuracy, reduce human error, and alleviate the workload on healthcare professionals, ultimately leading to better patient outcomes and more efficient clinical workflows. This review aims to highlight the current applications of artificial intelligence in addressing cardiovascular diseases
UR  - https://matjournals.net/engineering/index.php/JoDEKD/article/view/961
ER  -