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.