Artificial Intelligence in Cardiovascular Health: Insights into Post-COVID Public Health Challenges.
Authors
Affiliations (6)
Affiliations (6)
- Department of Biotechnology and Microbiology, School of Sciences, Noida International University, GautamBudh Nagar, Uttar Pradesh, 201308, India.
- Department of Mathematics, School of Sciences, Noida International University, GautamBudh Nagar, Uttar Pradesh, 201308, India.
- Department of Biotechnology, School of Engineering and Technology, Noida International University, GautamBudh Nagar, Uttar Pradesh, 201308, India.
- National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi, 110067, India.
- Information Technology Group CSIR-Centre for Cellular and Molecular Biology, Habsiguda, Uppal Road, Hyderabad, 500 007, Telangana, India. [email protected].
- Department of Biotechnology and Microbiology, School of Sciences, Noida International University, GautamBudh Nagar, Uttar Pradesh, 201308, India. [email protected].
Abstract
Cardiovascular diseases (CVDs) continue to be the topmost cause of the worldwide morbidity and mortality. Risk factors such as diabetes, hypertension, obesity and smoking are significantly worsening the situation. The COVID-19 pandemic has powerfully highlighted the undeniable connection between viral infections and cardiovascular health. Current literature highlights that SARS-CoV-2 contributes to myocardial injury, endothelial dysfunction, thrombosis, and systemic inflammation, increasing the severity of CVD outcomes. Long COVID has also been associated with persistent cardiovascular complications, including myocarditis, arrhythmias, thromboembolic events, and accelerated atherosclerosis. Addressing these challenges requires continued research and public health strategies to mitigate long-term risks. Artificial intelligence (AI) is changing cardiovascular medicine and community health through progressive machine learning (ML) and deep learning (DL) applications. AI enhances risk prediction, facilitates biomarker discovery, and improves imaging techniques such as echocardiography, CT, and MRI for detecting coronary artery disease and myocardial injury on time. Remote monitoring and wearable devices powered by AI enable real-time cardiovascular assessment and personalized treatment. In public health, AI optimizes disease surveillance, epidemiological modeling, and healthcare resource allocation. AI-driven clinical decision support systems improve diagnostic accuracy and health equity by enabling targeted interventions. The integration of AI into cardiovascular medicine and public health offers data-driven, efficient, and patient-centered solutions to mitigate post-COVID cardiovascular complications.