Artificial Intelligence (AI) in Cardiovascular Medicine
A special issue of Medical Sciences (ISSN 2076-3271). This special issue belongs to the section "Cardiovascular Disease".
Deadline for manuscript submissions: 1 October 2026 | Viewed by 57
Special Issue Editors
Interests: Preventive medicine; cardiology; AI; evidence based medicine
Special Issues, Collections and Topics in MDPI journals
Interests: cardiology; family medicine; preventive medicine
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide, underscoring the urgent need for strategies that enable early detection and timely intervention. Recent advances in artificial intelligence (AI) and machine learning offer transformative opportunities to improve cardiovascular health by enabling more accurate, efficient, and scalable diagnostic tools. From the automated analysis of imaging and electrocardiographic data to predictive modeling using electronic health records and wearable technologies, AI is reshaping how clinicians identify risk factors, detect early pathological changes, and guide personalized treatment strategies.
This Special Issue invites contributions that showcase innovative AI methodologies for early CVD detection, risk stratification, and prognosis. Topics of interest include—but are not limited to—deep learning for medical imaging, AI-powered biomarkers, data integration across multimodal sources, predictive analytics, explainable AI in clinical practice, and applications in digital health and remote monitoring. Both methodological advances and clinically oriented studies are welcome. By bringing together research at the intersection of AI and cardiovascular medicine, this Special Issue aims to accelerate progress toward earlier diagnosis and improved patient outcomes.
Dr. Nilima Rajpal Kundnani
Dr. Mihaela Adela Iancu
Guest Editors
Manuscript Submission Information
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Keywords
- cardiovascular diseases
- patient care
- preventive cardiology
- artificial intelligence
- machine learning
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