Main Article Content

Jawad Qammar
Muhammad Muneeb
Emad Munir
Muhammad Nabeel Javed
Rohma Ahmad Javed
Bilal Qammar


Cardiovascular disease, Artificial intelligence


AI has developed remarkable growth in the recent years and it has now gained importance in the area of cardiovascular disease. This study will focus on the role of cardiovascular disease and how AI is contributed towards it. So, the Systematic Literature review and meta-analysis will be done.

Abstract 170 | pdf Downloads 85


1. Alizadehsani, R., Khosravi, A., Roshanzamir, M., Abdar, M., Sarrafzadegan, N., Shafie, D., ... & Acharya, U. R. (2021). Coronary artery disease detection using artificial intelligence techniques: A survey of trends, geographical differences and diagnostic features 1991–2020. Computers in Biology and Medicine, 128, 104095.
2. Alsharqi, M., Woodward, W.J., Mumith, J.A., Markham, D.C., Upton, R. and Leeson, P., 2018. Artificial intelligence and echocardiography. Echo Research & Practice, 5(4), pp.R115-R125.
3. Baashar, Y., Alkawsi, G., Alhussian, H., Capretz, L. F., Alwadain, A., Alkahtani, A. A., & Almomani, M. (2022). Effectiveness of artificial intelligence models for cardiovascular disease prediction: network meta-analysis. Computational intelligence and neuroscience, 2022.
4. Bachtiger, P., Petri, C.F., Scott, F.E., Park, S.R., Kelshiker, M.A., Sahemey, H.K., Dumea, B., Alquero, R., Padam, P.S., Hatrick, I.R. and Ali, A., 2022. Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study. The Lancet Digital Health, 4(2), pp.e117-e125.
5. Bonkhoff, A.K. and Grefkes, C., 2022. Precision medicine in stroke: towards personalized outcome predictions using artificial intelligence. Brain, 145(2), pp.457-475.
6. Chen, K. W., Wang, Y. C., Liu, M. H., Tsai, B. Y., Wu, M. Y., Hsieh, P. H., ... & Chang, K. C. (2022). Artificial intelligence-assisted remote detection of ST-elevation myocardial infarction using a mini-12-lead electrocardiogram device in prehospital ambulance care. Frontiers in Cardiovascular Medicine, 9, 1001982.
7. Costal, D., Farré, C., Franch, X., & Quer, C. (2021). How tertiary studies perform quality assessment of secondary studies in software engineering. arXiv preprint arXiv:2110.03820.
8. Dell'Angela, L. and Nicolosi, G.L., 2022. Artificial intelligence applied to cardiovascular imaging, a critical focus on echocardiography: The point‐of‐view from “the other side of the coin”. Journal of Clinical Ultrasound, 50(6), pp.772-780.
9. Ghanayim, T., Lupu, L., Naveh, S., Bachner-Hinenzon, N., Adler, D., Adawi, S., Banai, S. and Shiran, A., 2022. Artificial intelligence-based stethoscope for the diagnosis of aortic stenosis. The American Journal of Medicine, 135(9), pp.1124-1133.
10. Grün, D., Rudolph, F., Gumpfer, N., Hannig, J., Elsner, L. K., von Jeinsen, B., ... & Keller, T. (2021). Identifying heart failure in ECG data with artificial intelligence—a meta-analysis. Frontiers in Digital Health, 2, 584555.
11. Haq, I.U., Chhatwal, K., Sanaka, K. and Xu, B., 2022. Artificial intelligence in cardiovascular medicine: current insights and future prospects. Vascular Health and Risk Management, pp.517-528.
12. Jone, P.N., Gearhart, A., Lei, H., Xing, F., Nahar, J., Lopez-Jimenez, F., Diller, G.P., Marelli, A., Wilson, L., Saidi, A. and Cho, D., 2022. Artificial Intelligence in Congenital Heart Disease: Current State and Prospects. JACC: Advances, 1(5), p.100153.
13. Kwon, J.M., Kim, K.H., Akkus, Z., Jeon, K.H., Park, J. and Oh, B.H., 2020. Artificial intelligence for detecting mitral regurgitation using electrocardiography. Journal of electrocardiology, 59, pp.151-157.
14. Lareyre, F., Lê, C. D., Ballaith, A., Adam, C., Carrier, M., Amrani, S., ... & Raffort, J. (2022). Applications of artificial intelligence in non-cardiac vascular diseases: a bibliographic analysis. Angiology, 73(7), 606-614.
15. Lee, S., Chu, Y., Ryu, J., Park, Y. J., Yang, S., & Koh, S. B. (2022). Artificial intelligence for detection of cardiovascular-related diseases from wearable devices: a systematic review and meta-analysis. Yonsei medical journal, 63(Suppl), S93.
16. Lee, S., Chu, Y., Ryu, J., Park, Y.J., Yang, S. and Koh, S.B., 2022. Artificial intelligence for detection of cardiovascular-related diseases from wearable devices: a systematic review and meta-analysis. Yonsei medical journal, 63(Suppl), p.S93.
17. Li, S., Wang, Z., Visser, L.C., Wisner, E.R. and Cheng, H., 2020. Pilot study: application of artificial intelligence for detecting left atrial enlargement on canine thoracic radiographs. Veterinary radiology & ultrasound, 61(6), pp.611-618.
18. Lv, J., Dong, B., Lei, H., Shi, G., Wang, H., Zhu, F., Wen, C., Zhang, Q., Fu, L., Gu, X. and Yuan, J., 2021. Artificial intelligence-assisted auscultation in detecting congenital heart disease. European Heart Journal-Digital Health, 2(1), pp.119-124.
19. Mathur, P., Srivastava, S., Xu, X. and Mehta, J.L., 2020. Artificial intelligence, machine learning, and cardiovascular disease. Clinical Medicine Insights: Cardiology, 14, p.1179546820927404.
20. Nedadur, R., Wang, B., & Tsang, W. (2022). Artificial intelligence for the echocardiographic assessment of valvular heart disease. Heart, 108(20), 1592-1599.
21. Ranka, S., Reddy, M., & Noheria, A. (2021). Artificial intelligence in cardiovascular medicine. Current Opinion in Cardiology, 36(1), 26-35.
22. Ribeiro, J.M., Astudillo, P., de Backer, O., Budde, R., Nuis, R.J., Goudzwaard, J., Van Mieghem, N.M., Lumens, J., Mortier, P., Mattace-Raso, F. and Boersma, E., 2022. Artificial intelligence and transcatheter interventions for structural heart disease: a glance at the (near) future. Trends in cardiovascular medicine, 32(3), pp.153-159.
23. Roy, T.S., Roy, J.K. and Mandal, N., 2022. Classifier identification using deep learning and machine learning algorithms for the detection of valvular heart diseases. Biomedical Engineering Advances, 3, p.100035.
24. Sameer Mehta, M. D., Mario Alberto Torres, M. D., Isabella Vallenilla, M. D., Maria Angelica Marin, M. D., Maria Isabel Acosta, M. D., Claudia Lopez, M. D., ... & Benjamin Wood, M. D. (2019). Artificial Intelligence: Refining STEMI Interventions.
25. Seetharam, K., Raina, S. and Sengupta, P.P., 2020. The role of artificial intelligence in echocardiography. Current Cardiology Reports, 22, pp.1-8.
26. Singh, K.K. and Singh, S.S., 2019, July. An Artificial Intelligence based mobile solution for early detection of valvular heart diseases. In 2019 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) (pp. 1-5). IEEE.
27. Siontis, K. C., Noseworthy, P. A., Attia, Z. I., & Friedman, P. A. (2021). Artificial intelligence-enhanced electrocardiography in cardiovascular disease management. Nature Reviews Cardiology, 18(7), 465-478.
28. Thoenes, M., Agarwal, A., Grundmann, D., Ferrero, C., McDonald, A., Bramlage, P. and Steeds, R.P., 2021. Narrative review of the role of artificial intelligence to improve aortic valve disease management. Journal of Thoracic Disease, 13(1), p.396.
29. Ueda, D., Matsumoto, T., Ehara, S., Yamamoto, A., Walston, S.L., Ito, A., Shimono, T., Shiba, M., Takeshita, T., Fukuda, D. and Miki, Y., 2023. Artificial intelligence-based model to classify cardiac functions from chest radiographs: a multi-institutional, retrospective model development and validation study. The Lancet Digital Health, 5(8), pp.e525-e533.
30. Wang, H., Zu, Q., Chen, J., Yang, Z. and Ahmed, M.A., 2021. Application of artificial intelligence in acute coronary syndrome: a brief literature review. Advances in Therapy, pp.1-9.
31. Xu, B., Kocyigit, D., Grimm, R., Griffin, B.P. and Cheng, F., 2020. Applications of artificial intelligence in multimodality cardiovascular imaging: a state-of-the-art review. Progress in cardiovascular diseases, 63(3), pp.367-376.
32. Yasmin, F., Shah, S. M. I., Naeem, A., Shujauddin, S. M., Jabeen, A., Kazmi, S., ... & Lak, H. M. (2021). Artificial intelligence in the diagnosis and detection of heart failure: the past, present, and future. Reviews in Cardiovascular Medicine, 22(4), 1095-1113.