In the healthcare domain, a digital twin (DT) serves as a digital representation of either a patient or an entire healthcare system, integrating simulations and service data. This digital twin actively monitors a patient's records, cross-referencing them against established patterns, and conducting analyses for potential diseases or contraindications. Utilizing adaptive analytics and advanced algorithms, the digital twin provides accurate prognoses and recommends suitable interventions. By simulating various medical scenarios before initiating treatment, the digital twin enhances patient safety and ensures the delivery of the most appropriate treatments tailored to individual patient requirements.
Metaverse Technologies (MT) in healthcare are centered around data analysis, harnessing the potential of data to enhance the effectiveness of healthcare organizations. While healthcare services aim to uphold the physical, mental, social, and emotional well-being of human lives, the Metaverse combines technological trends—Artificial Intelligence (AI), Augmented Reality (AR), and Virtual Reality (VR). Collectively, these technologies have the capacity to deliver treatments and medicines, reduce costs, and significantly improve patient outcomes.
This book explores the integration of the digital twin and metaverse concepts with other technologies such as artificial intelligence (AI), machine learning (ML), big data analytics, IoT, and cloud data management to enhance healthcare systems and processes. The focus extends to various research perspectives and challenges in implementing DT and MT concerning data analysis, cloud management, and data privacy issues. With chapters covering visualization techniques, prognostics, and health management, this book is essential for researchers, engineers, and IT professionals in healthcare, as well as those involved in utilizing DT, MT, AI, IoT, and big data analytics for innovative applications.