Review Role of Ai in Early Detection and Treatment of Cardiovascular Diseases

Cardiovascular diseases cause morbidity and mortality. Early detection is critical, as it can detect and the use of AI plays a significant role in and impacts cardiovascular diseases. Since cardiovascular diseases (CVDs) continue to be the world's leading cause of death, improvements in early diagnosis, treatment, and management techniques are vital. The integration of artificial intelligence (AI), machine learning, and deep learning into cardiovascular medicine offers promising avenues to improve patient outcomes. This review explores recent progress in AI applications for CVDs, including automated electrocardiogram (ECG) analysis, medical imaging, wearable sensor technologies, and telemedicine. AI-driven systems have demonstrated potential in enhancing diagnostic accuracy, enabling remote monitoring, predicting disease risk, and supporting clinical decision-making. Despite significant advancements, challenges such as data bias, algorithmic fairness, and the need for rigorous clinical validation remain. Continued research and the responsible deployment of AI technologies can help address the global burden of CVDs through more precise, efficient, and personalized care.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-02
DOI
https://doi.org/10.5281/zenodo.16719087
Primary Topic
Medical Imaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

Review Role of Ai in Early Detection and Treatment of Cardiovascular Diseases

Zenodo (CERN European Organization for Nuclear Research)
Medical Imaging Techniques and Applications
article

Review Role of Ai in Early Detection and Treatment of Cardiovascular Diseases

article en

Abstract

Cardiovascular diseases cause morbidity and mortality. Early detection is critical, as it can detect and the use of AI plays a significant role in and impacts cardiovascular diseases. Since cardiovascular diseases (CVDs) continue to be the world's leading cause of death, improvements in early diagnosis, treatment, and management techniques are vital. The integration of artificial intelligence (AI), machine learning, and deep learning into cardiovascular medicine offers promising avenues to improve patient outcomes. This review explores recent progress in AI applications for CVDs, including automated electrocardiogram (ECG) analysis, medical imaging, wearable sensor technologies, and telemedicine. AI-driven systems have demonstrated potential in enhancing diagnostic accuracy, enabling remote monitoring, predicting disease risk, and supporting clinical decision-making. Despite significant advancements, challenges such as data bias, algorithmic fairness, and the need for rigorous clinical validation remain. Continued research and the responsible deployment of AI technologies can help address the global burden of CVDs through more precise, efficient, and personalized care.

Zenodo (CERN European Organization for Nuclear Research)
Osmania University (IN)
Good health and well-being
Openalex Percentile: Top 40%
Medical Imaging Techniques and Applications
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Review Role of Ai in Early Detection and Treatment of Cardiovascular Diseases · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS