The Role of Artificial Intelligence in Cardiology

Artificial intelligence (AI) is revolutionizing cardiovascular medicine by significantly enhancing diagnostic precision and predictive capabilities. In electrocardiography (ECG), AI demonstrates superior sensitivity and accuracy compared to traditional methods, efficiently detecting conditions such as atrial fibrillation, subtle ST-segment changes, QT prolongation, and even asymptomatic left ventricular dysfunction. Recent studies underscore AI’s potential in identifying rhythm abnormalities through consumer-grade devices, enabling real-time monitoring and early intervention. However, limitations persist, notably the reliance on retrospective data and limited follow-up periods. Cardiovascular imaging, including echocardiography, coronary CT angiography, and cardiac MRI, also benefits substantially from AI applications. AI systems effectively interpret echocardiograms with comparable accuracy to experienced cardiologists, significantly reducing analysis time. Similarly, coronary CT angiography enhanced by AI demonstrates high sensitivity in identifying coronary artery disease. AI-driven cardiac MRI analysis accelerates image processing from minutes to seconds, maintaining diagnostic accuracy. In cardiovascular risk prediction, AI-driven models have consistently outperformed traditional risk assessment tools. AI achieves higher accuracy in predicting heart failure hospitalizations and post-myocardial infarction survival by integrating multifaceted patient data, though current evidence largely stems from retrospective analyses predominantly involving limited demographic groups. In conclusion, AI holds considerable promise for improving cardiovascular diagnosis and personalized risk prediction. Future clinical integration necessitates comprehensive prospective studies to confirm reliability and address ethical considerations, particularly regarding patient data privacy.

Authors

Institutions

Publication Details

Journal
Journal of The Best Available Evidence in Medicine
Published
2025-04-26
DOI
https://doi.org/10.63720/9mv0pjhr
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Role of Artificial Intelligence in Cardiology

Ibrahim Elhaddar
Journal of The Best Available Evidence in Medicine
Artificial Intelligence in Healthcare and Education
article

The Role of Artificial Intelligence in Cardiology

Ibrahim Elhaddar
article en

Abstract

Artificial intelligence (AI) is revolutionizing cardiovascular medicine by significantly enhancing diagnostic precision and predictive capabilities. In electrocardiography (ECG), AI demonstrates superior sensitivity and accuracy compared to traditional methods, efficiently detecting conditions such as atrial fibrillation, subtle ST-segment changes, QT prolongation, and even asymptomatic left ventricular dysfunction. Recent studies underscore AI’s potential in identifying rhythm abnormalities through consumer-grade devices, enabling real-time monitoring and early intervention. However, limitations persist, notably the reliance on retrospective data and limited follow-up periods. Cardiovascular imaging, including echocardiography, coronary CT angiography, and cardiac MRI, also benefits substantially from AI applications. AI systems effectively interpret echocardiograms with comparable accuracy to experienced cardiologists, significantly reducing analysis time. Similarly, coronary CT angiography enhanced by AI demonstrates high sensitivity in identifying coronary artery disease. AI-driven cardiac MRI analysis accelerates image processing from minutes to seconds, maintaining diagnostic accuracy. In cardiovascular risk prediction, AI-driven models have consistently outperformed traditional risk assessment tools. AI achieves higher accuracy in predicting heart failure hospitalizations and post-myocardial infarction survival by integrating multifaceted patient data, though current evidence largely stems from retrospective analyses predominantly involving limited demographic groups. In conclusion, AI holds considerable promise for improving cardiovascular diagnosis and personalized risk prediction. Future clinical integration necessitates comprehensive prospective studies to confirm reliability and address ethical considerations, particularly regarding patient data privacy.

Journal of The Best Available Evidence in MedicineVol. 1(1)
Libyan International Medical University (LY), University of Edinburgh (GB)
Openalex Percentile: Top 95%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

The Role of Artificial Intelligence in Cardiology — Ibrahim Elhaddar · Journal of The Best Available Evidence in Medicine (2025) | TGRS Research Map | TGRS