The Role of Artificial Intelligence and Machine Learning in Cardiovascular Imaging and Diagnosis: Current Insights and Future Directions

Cardiovascular diseases (CVDs) are the major cause of mortality worldwide, emphasizing the critical need for timely and accurate diagnosis. Artificial intelligence (AI) and machine learning (ML) have become revolutionary tools in the healthcare system with significant potential for cardiovascular di...

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Bibliographic Details
Published in:Curēus (Palo Alto, CA) CA), 2024-10, Vol.16 (10), p.e72311
Main Authors: Cerdas, Maria Gabriela, Pandeti, Sucharitha, Reddy, Likhitha, Grewal, Inayat, Rawoot, Asiya, Anis, Samia, Todras, Jade, Chouihna, Sami, Salma, Saba, Lysak, Yuliya, Khan, Saad Ahmed
Format: Article
Language:English
Subjects:
Artificial intelligence
Automation
Cardiology
Cardiovascular disease
Decision making
Healthcare Technology
Medical diagnosis
Radiology
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Summary:Cardiovascular diseases (CVDs) are the major cause of mortality worldwide, emphasizing the critical need for timely and accurate diagnosis. Artificial intelligence (AI) and machine learning (ML) have become revolutionary tools in the healthcare system with significant potential for cardiovascular diagnosis and imaging. AI and ML techniques, including supervised and unsupervised learning, logistic regression, deep learning models, neural networks, and convolutional neural networks (CNNs), have significantly advanced cardiovascular imaging. Applications in echocardiography include left and right ventricular segmentation, ejection fraction measurement, and wall motion analysis. AI and ML hold substantial promise for revolutionizing cardiovascular imaging, demonstrating improvements in diagnostic accuracy and efficiency. This narrative review aims to explore the current applications, advantages, challenges, and future pathways of AI and ML in cardiovascular imaging, highlighting their impact on different imaging modalities and their integration into clinical practice.
ISSN:2168-8184
2168-8184
DOI:10.7759/cureus.72311