Digital Twin Technologies for Healthcare 4.0
Institution of Engineering and Technology (Verlag)
978-1-83953-579-6 (ISBN)
In healthcare, a digital twin is a digital representation of a patient or healthcare system using integrated simulations and service data. The digital twin tracks a patient's records, crosschecks them against registered patterns and analyses any diseases or contra indications. The digital twin uses adaptive analytics and algorithms to produce accurate prognoses and suggest appropriate interventions. A digital twin can run various medical scenarios before treatment is initiated on the patient, thus increasing patient safety as well as providing the most appropriate treatments to meet the patient's requirements.
Digital Twin Technologies for Healthcare 4.0 discusses how the concept of the digital twin can be merged with other technologies, such as artificial intelligence (AI), machine learning (ML), big data analytics, IoT and cloud data management, for the improvement of healthcare systems and processes. The book also focuses on the various research perspectives and challenges in implementation of digital twin technology in terms of data analysis, cloud management and data privacy issues.
With chapters on visualisation techniques, prognostics and health management, this book is a must-have for researchers, engineers and IT professionals in healthcare as well as those involved in using digital twin technology, AI, IoT and big data analytics for novel applications.
Rajesh Kumar Dhanaraj is a professor in the School of Computing Science and Engineering at Galgotias University, India. He has contributed 35+ authored and edited books, 21 patents and 68 articles and papers in various journals and international conferences. He is a senior member of the IEEE, member of the Computer Science Teacher Association (CSTA); and International Association of Engineers (IAENG). His research interests include machine learning, cyber-physical systems and wireless sensor networks. Santhiya Murugesan is an assistant professor at Kongu Engineering College, India. She completed her Bachelor of Engineering in electronics and instrumentation in 2012 and did her master's degree in instrumentation engineering at Madras Institute of Technology in 2014. Her specialisation areas include internet of things, sensors and transducers and process modelling. Recently, she has been pursuing research in the area of autonomous underwater vehicles. Balamurugan Balusamy is the associate dean for students at Shiv Nadar University, Delhi-NCR, India. Prior to this he was a professor in the School of Computing Sciences & Engineering and director of international relations at Galgotias University, India. He has contributed to 80+ edited and authored books and has 200+ high impact factor papers. He has given over 195 talks at various conferences, events and symposiums. His research areas include blockchain and IoT. Valentina E. Balas is a professor in the Department of Automatics and Applied Software at the University "Aurel Vlaicu" Arad, Romania. She has authored 140+ research papers in journals and conferences. She is a member of numerous editorial boards and is the editor-in chief of the International Journal of Advanced Intelligence Paradigms (IJAIP). Her research interests include intelligent systems, fuzzy control, soft computing, smart sensors, information fusion, modelling and simulation, electronics, measurements and system theory.
Chapter 1: Introduction: digital twin technology in healthcare
Chapter 2: Convergence of Digital Twin, AI, IOT, and machine learning techniques for medical diagnostics
Chapter 3: Application of digital twin technology in model-based systems engineering
Chapter 4: Digital twins in e-health: adoption of technology and challenges in the management of clinical systems
Chapter 5: Digital twin and big data in healthcare systems
Chapter 6: Digital twin data visualization techniques
Chapter 7: Healthcare cyberspace: medical cyber physical system in digital twin
Chapter 8: Cloud security-enabled digital twin in e-healthcare
Chapter 9: Digital twin in prognostics and health management system
Chapter 10: Deep learning in Covid-19 detection and diagnosis using CXR images: challenges and perspectives
Chapter 11: Case study: digital twin in cardiology
| Erscheinungsdatum | 16.05.2023 |
|---|---|
| Reihe/Serie | Healthcare Technologies |
| Verlagsort | Stevenage |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Medizin / Pharmazie ► Gesundheitswesen | |
| ISBN-10 | 1-83953-579-2 / 1839535792 |
| ISBN-13 | 978-1-83953-579-6 / 9781839535796 |
| Zustand | Neuware |
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