Abstract
There has been an increase in the implementation of digital twin (DT) technology in several sectors, including healthcare, which is crucial in revolutionizing patient care, medical research, and hospital operations. This chapter explores the implementation of DTs in real-world healthcare scenarios, emphasizing predictive maintenance, patient flow optimization, and inventory management. Hospitals can create dynamic virtual replicas of medical devices, infrastructure, and human physiology by leveraging the Internet of things, cloud computing, and artificial intelligence-driven analytics to enhance decision-making. The chapter also highlights case studies for DT implementation, best practices for implementation, and the future of DTs in sustainable healthcare. DT promises to improve operational efficiency, reduce costs, and elevate patient outcomes in modern healthcare systems through continuous monitoring and real-time insights.
| Original language | English |
|---|---|
| Title of host publication | Digital Twins for Sustainable Development |
| Publisher | Elsevier |
| Pages | 63-101 |
| Number of pages | 39 |
| ISBN (Electronic) | 9780443273889 |
| ISBN (Print) | 9780443273896 |
| DOIs | |
| Publication status | Published - 01-01-2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- General Computer Science
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