Open Access

Impact of artificial intelligence and digital twin technology on cardiovascular disease diagnosis and management challenges and future directions (Review)

  • Authors:
    • Ann Steffi Sharon John
    • Sriram Alagendran
    • Balamurugan Sivaprakasam
    • Mirudhula Kamakshi Mohan Ramaswamy
    • Karthick Selvaraj
    • Sharmila Ramanathan
    • Punitha Velam Chokkalingam
    • Nevetha Ravindran
    • Suvaithenamudhan Suvaiyarasan
  • View Affiliations

  • Published online on: June 16, 2025     https://doi.org/10.3892/wasj.2025.363
  • Article Number: 75
  • Copyright : © Sharon John et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY 4.0].

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

The incidence of cardiovascular disease (CVD) is rising steadily and continues to be the major cause of mortality worldwide. The pressing requirement is to develop personalised healthcare solutions. Digital twin (DT) and artificial intelligence (AI) technology can change the treatment of CV through personal disease modelling, risk stratification, diagnosis and prediction. AI‑powered DT technologies develop patient‑specific simulations that aid in early diagnosis, optimized treatment and post‑intervention monitoring. Machine learning algorithms and deep neural networks enable real‑time data identity from electronic health records, portable sensors and medical imaging to continuously update digital twins to represent physiological changes. AI‑powered DT models also help in better clinical decision‑making by modelling disease progression and accurately predicting treatment outcomes. However, its universal adoption is hampered by issues of data privacy concerns, computational power requirements, and regulatory compliance. Strengthening these capabilities using good data stewardship, interdisciplinarity and next‑generation computational architectures will accelerate the use of DT technology in cardiovascular medicine. The present review emphasizes the applications of AI‑based DT models to correct the future of accurate cardiology, pursue the patient's results and reduce the burden of health care.
View Figures
View References

Related Articles

Journal Cover

July-August 2025
Volume 7 Issue 4

Print ISSN: 2632-2900
Online ISSN:2632-2919

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
x
Spandidos Publications style
Sharon John A, Alagendran S, Sivaprakasam B, Mohan Ramaswamy M, Selvaraj K, Ramanathan S, Velam Chokkalingam P, Ravindran N and Suvaiyarasan S: Impact of artificial intelligence and digital twin technology on cardiovascular disease diagnosis and management challenges and future directions (Review). World Acad Sci J 7: 75, 2025.
APA
Sharon John, A., Alagendran, S., Sivaprakasam, B., Mohan Ramaswamy, M., Selvaraj, K., Ramanathan, S. ... Suvaiyarasan, S. (2025). Impact of artificial intelligence and digital twin technology on cardiovascular disease diagnosis and management challenges and future directions (Review). World Academy of Sciences Journal, 7, 75. https://doi.org/10.3892/wasj.2025.363
MLA
Sharon John, A., Alagendran, S., Sivaprakasam, B., Mohan Ramaswamy, M., Selvaraj, K., Ramanathan, S., Velam Chokkalingam, P., Ravindran, N., Suvaiyarasan, S."Impact of artificial intelligence and digital twin technology on cardiovascular disease diagnosis and management challenges and future directions (Review)". World Academy of Sciences Journal 7.4 (2025): 75.
Chicago
Sharon John, A., Alagendran, S., Sivaprakasam, B., Mohan Ramaswamy, M., Selvaraj, K., Ramanathan, S., Velam Chokkalingam, P., Ravindran, N., Suvaiyarasan, S."Impact of artificial intelligence and digital twin technology on cardiovascular disease diagnosis and management challenges and future directions (Review)". World Academy of Sciences Journal 7, no. 4 (2025): 75. https://doi.org/10.3892/wasj.2025.363