CARDIOVASCULAR DISEASE AND THE ROLE OF ARTIFICIAL INTELLIGENCE: LITERATURE REVIEW
Main Article Content
Keywords
Cardiovascular Disease, Artificial Intelligence, Machine Learning, Risk Assessment, Predictive Analytics
Abstract
Background: Cardiovascular diseases (CVDs) remain a leading global health issue, with increasing prevalence and economic impact. This study systematically reviews the current literature on CVD prevalence, prevention, management strategies, and the integration of artificial intelligence (AI) in cardiovascular medicine.
Methods: A comprehensive literature search was conducted using databases such as PubMed and Google Scholar. Studies were screened for relevance, and data were synthesized to evaluate trends, interventions, and AI applications in cardiovascular care.
Results: The review found a rising prevalence of CVDs and substantial economic burden. Behavioral interventions, including weight loss and dietary counseling, are effective in reducing cardiovascular risk. AI has shown potential in enhancing diagnostic accuracy and personalizing treatment, though challenges in validation and implementation remain.
Conclusion: Addressing the growing burden of CVDs requires effective prevention strategies and the integration of validated AI tools into clinical practice. Future research should focus on optimizing these approaches and assessing their cost-effectiveness to improve cardiovascular health outcomes and reduce healthcare costs.
References
2. Barkas, F., et al. (2024). "Advancements in risk stratification and management strategies in primary cardiovascular prevention." Atherosclerosis 395: 117579.
3. Brunham, L. R., et al. (2024). "Dyslipidemia and the Current State of Cardiovascular Disease: Epidemiology, Risk Factors, and Effect of Lipid Lowering." Canadian Journal of Cardiology 40(8): S4-S12.
4. Chan, P. Z., Ramli, M. A., & Chew, H. S. (2023). Diagnostic test accuracy of artificial intelligence-assisted detection of acute coronary syndrome: a systematic review and meta-analysis. Comput Biol Med, 167, 107636.
5. Ciccarelli, M., Giallauria, F., Carrizzo, A., et al. (2023). Artificial intelligence in cardiovascular prevention: new ways will open new doors. J Cardiovasc Med (Hagerstown), 24, 0–15.
6. Curry, S. J., Krist, A. H., Owens, D. K., et al. (2018). Behavioral weight loss interventions to prevent obesity-related morbidity and mortality in adults: US Preventive Services Task Force recommendation statement. JAMA, 320, 1163–1171.
7. Giannitsis, E., Kurz, K., Hallermayer, K., et al. (2010). Analytical validation of a high-sensitivity cardiac troponin T assay. Clin Chem, 56, 254–261.
8. Hussain, M. M., et al. (2024). "Risk Factors Associated with Cardiovascular Disorders: Risk Factors Associated with Cardiovascular Disorders." Pakistan BioMedical Journal: 03-10.
9. Koulaouzidis, G., Jadczyk, T., Iakovidis, D. K., et al. (2022). Artificial intelligence in cardiology-a narrative review of current status. J Clin Med, 11, 3910.
10. Manolis, A. A., Manolis, T. A., Melita, H., & Manolis, A. S. (2023). Features of a balanced healthy diet with cardiovascular and other benefits. Curr Vasc Pharmacol, 21, 163–184.
11. Mensah, G. A., Fuster, V., Murray, C. J., & Roth, G. A. (2023). Global burden of cardiovascular diseases and risks, 1990-2022. J Am Coll Cardiol, 82, 2350–2473.
12. Nazir, M. B. and I. Hussain (2024). "Revolutionizing Cardiac Care: AI and Deep Learning in Heart Health." International Journal of Advanced Engineering Technologies and Innovations 1(4): 189-208.
13. Nelson, S., Whitsel, L., Khavjou, O., et al. (2024). Projections of Cardiovascular Disease Prevalence and Costs: 2015-2035. American Heart Association.
14. Roger, V. L., Sidney, S., Fairchild, A. L., et al. (2020). Recommendations for cardiovascular health and disease surveillance for 2030 and beyond: a policy statement from the American Heart Association. Circulation, 141, 0–19.
15. Samuel, P. O., et al. (2024). "Lifestyle modifications for preventing and managing cardiovascular diseases." Sport Sciences for Health 20(1): 23-36.
16. Sun, X., Yin, Y., Yang, Q., & Huo, T. (2023). Artificial intelligence in cardiovascular diseases: diagnostic and therapeutic perspectives. Eur J Med Res, 28, 242.