Cloud-Based Digital Twins: Revolutionizing Healthcare Monitoring and Management: A Comprehensive Review

Authors

  • Rubeel Taj PG Scholor, Department of Computer Science and Engineering, Integral University, Lucknow, India
  • Aaftab Alam Assistant Professor, Department of Computer Science and Engineering, Integral University, Lucknow, India
  • Falak Alam Assistant Professor, Department of Computer Science and Engineering, Integral University, Lucknow, India
  • Mohd Haroon Professor, Department of Computer Science and Engineering, Integral University, Lucknow, India

Keywords:

Cloud-based digital twins, Healthcare monitoring, Healthcare management, Real-time data analytics, Predictive diagnostics, Personalized medicine, Remote patient monitoring, Medical device optimization, Healthcare workflow efficiency, Artificial intelligence in healthcare, Machine learning in digital twins, Data security in healthcare, Interoperability in healthcare systems, Smart healthcare systems , Healthcare technology innovation

Abstract

The rapid evolution of healthcare technology has led to innovative solutions for addressing challenges in patient care, operational efficiency, and data management. Among these, cloud-based digital twins have emerged as a transformative technology, offering real-time, data-driven models that mirror physical entities such as patients, medical devices, or healthcare processes. This comprehensive review explores the integration of digital twin technology with cloud computing in the healthcare industry, highlighting its potential to revolutionize monitoring and management practices.

Cloud infrastructure enables the seamless collection, storage, and processing of vast amounts of healthcare data, empowering digital twins to provide real-time insights into patient health, predictive diagnostics, and personalized treatment plans. Furthermore, the review examines the role of cloud-based digital twins in optimizing hospital workflows, improving the efficiency of medical devices, and enabling remote patient monitoring.

Key challenges such as data security, interoperability, and the computational demands of integrating digital twins with existing healthcare systems are discussed alongside potential solutions. The study also outlines current applications and emerging trends, emphasizing the role of artificial intelligence and machine learning in enhancing the capabilities of digital twins.

Ultimately, this review underscores the transformative potential of cloud-based digital twins in fostering a patient-centric, data-driven healthcare ecosystem, paving the way for smarter and more efficient healthcare delivery systems.

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Published

2025-01-02

How to Cite

[1]
Rubeel Taj, Aaftab Alam, Falak Alam, and Mohd Haroon, “Cloud-Based Digital Twins: Revolutionizing Healthcare Monitoring and Management: A Comprehensive Review”, IJIRCST, vol. 13, no. 1, pp. 19–25, Jan. 2025.

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