Digital Twins and Predictive Modeling in Robotic Surgery

Erscheinungsjahr 2027
ISBN: 978-0-443-45470-7
Verlag: Elsevier Science

Buch, Englisch, 350 Seiten, Format (B × H): 191 mm x 235 mm

Digital Twins and Predictive Modeling in Robotic Surgery addresses the transformative convergence of digital twin technology, predictive analytics, and robotic surgery. This reference responds to the critical need for a comprehensive resource that bridges simulation science, artificial intelligence, and real-time robotic execution, facilitating enhanced surgical precision, patient-specific planning, and intraoperative decision-making. The content is organized into four parts covering foundational intelligent surgical systems, predictive modeling and simulation, clinical applications with case studies, and challenges alongside future directions. Topics include AI integration, IoT-enabled sensor networks, digital twin architectures encompassing the entire surgical ecosystem, surgical workflow modeling, risk assessment, human-robot interaction, technology acceptance, ethical and regulatory considerations. Real-world examples from smart hospitals worldwide illustrate practical implementation. This books benefits biomedical engineers, researchers, and healthcare system architects by providing interdisciplinary insights, practical implementation frameworks, and cutting-edge case studies. It supports improved surgical planning, precision, and decision-making, empowering end users to advance the adoption of intelligent, AI-powered robotic surgery systems in clinical practice and research environments.

Autoren/Hrsg.

Khan, Mudassir

Prasad, Arun

Dey, Rajesh

Mahajan, Rupali Atul

Fachgebiete

• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie

Inhaltsverzeichnis

PART I: Foundations of Intelligent Surgical Systems
1. Introduction to Digital Surgery and the Smart Operating Room
2. Principles of Robotic Surgery and System Design
3. Artificial Intelligence in Surgical Practice
4. Internet of Medical Things (IoMT) and Sensor Networks
5. Digital Twin Architecture for Surgery
6. Regulatory Frameworks and Standards in Surgical AI and Robotics

PART II: Predictive Modeling and Simulation in Surgery
7. Data-Driven Surgical Workflow Modeling
8. Predictive Analytics for Risk Assessment and Outcome Forecasting
9. Integration of Digital Twins with Real-Time Surgical Systems
10. Practical Implementation of Surgical Digital Twins

PART III: Human Factors, Ethics, and Technology Adoption
11. Human-Computer Interaction (HCI) in Surgical AI Systems
12. Ethical AI in Robotic Surgery
13. Technology Acceptance in Surgical AI Systems PART IV: Advanced Applications and Future Directions
14. Robotic-Assisted Surgery for Complex Procedures
15. AI in Personalized Surgical Care and Precision Medicine
16. Multimodal Data Fusion in Surgical Environments
17. Future Trends: Autonomous Surgery and Beyond Appendices and Supplementary Materials

Glossary of Key Terms Datasets and Performance Benchmarks Multimedia Resources and Instructional Videos

Über Autor(innen)

Prasad, Arun
Dr. Arun Prasad is a globally acclaimed surgeon with over 36 years of experience in laparoscopic, bariatric, thoracoscopic, endoscopic, and robotic surgery. He has performed more than 10,000 advanced laparoscopic procedures and holds distinguished qualifications including MBBS (AFMC), MS (MAMC), dual FRCS (UK), and FACS (USA).

A pioneer in minimally invasive and robotic surgery, Dr. Prasad was among the first surgeons worldwide to perform procedures such as day-care laparoscopic cholecystectomy, thoracoscopic hydatid cyst excision, and single incision laparoscopic surgery (SILS). He has achieved several world-first robotic surgeries, including the robotic mini gastric bypass and robotic pancreatic surgery, underscoring his leadership in developing surgical robotics techniques and applications.

Dr. Prasad has held prominent roles including President of the Obesity Surgery Society of India (OSSI) and Vice President of the Indian Association of Gastrointestinal Endo Surgeons (IAGES). He serves as an editor for leading surgical journals and sits on boards of international surgical organizations. Through fellowships like FALS, FIAGES, and FIBC, he has trained surgeons across India and globally, fostering expertise in minimally invasive and robotic surgery.

His clinical and research interests include bariatric surgery, robotic surgery, video-assisted thoracoscopic surgery (VATS), and advanced gastrointestinal procedures. Dr. Prasad has published extensively in peer-reviewed journals and is a sought-after speaker at international conferences and surgical workshops.

His pioneering work continues to advance surgical robotics, bridging clinical innovation and biomedical engineering to improve patient care.

Mahajan, Rupali Atul
Dr. Rupali Atul Mahajan is an Associate Professor and Head of the Data Science Department in the Computer Science and Engineering faculty at Vishwakarma Institute of Technology (VIIT), Pune, India. She also serves as the Associate Dean of Research and Development at VIIT. Dr. Mahajan holds a PhD in Computer Science and Engineering, with research interests spanning machine learning, artificial intelligence (AI), and deep learning.

With a prolific academic career, she has authored seven books and published over 50 research papers in reputed journals and conferences. Dr. Mahajan actively engages in consultancy projects with the Government of Maharashtra, leveraging her expertise to address real-world challenges. Her collaborative work extends internationally, partnering with institutions such as Lincoln University College, National Kaohsiung University of Science and Technology (Taiwan), and IIT Mandi Catalyst.

A passionate educator and technologist, Dr. Mahajan is deeply committed to advancing education and research in data science and AI. She regularly contributes as a keynote speaker and mentor, fostering innovation and knowledge sharing across academic and industry platforms. Her leadership roles at VIIT reflect her dedication to nurturing research initiatives and guiding the next generation of technology professionals.

Dr. Mahajan’s contributions continue to impact the fields of machine learning and AI significantly, making her a respected figure in both national and international scientific communities.

Dey, Rajesh
Dr. Rajesh Dey is a distinguished researcher, educator, and industry expert specializing in artificial intelligence (AI), machine learning (ML), and financial technology (FinTech). He is currently a Postdoctoral Fellow at IIUM, Malaysia, focusing on AI and ML applications in FinTech, with expertise in computer simulations and signal processing. Dr. Dey earned his PhD in Adaptive Signal Correction from Maulana Abul Kalam Azad University of Technology, West Bengal.

With over 17 years of research and development experience, Dr. Dey has published extensively in reputable journals and conferences. He has held notable academic and industry positions, including Associate Professor at Gopal Narayan Singh University, Technical Director at The Electroinventor, and Adjunct Researcher at Perdana University Malaysia. His multidisciplinary work spans embedded systems, robotics, IoT, and sustainable electric vehicle technologies, driving innovation across these areas.

As a certified Design Thinking Coach and mentor, Dr. Dey collaborates with universities and research institutions worldwide, such as Lincoln University College, National Kaohsiung University of Science and Technology (Taiwan), and IIT Mandi Catalyst. His passion for technology and education fuels his role as a keynote speaker and mentor in both academic and industry settings.

Khan, Mudassir
Dr. Mudassir Khan is an Assistant Professor at King Khalid University, Saudi Arabia, with extensive experience in teaching and research in computer science and data analytics. His work focuses on Big Data, artificial intelligence, machine learning, deep learning, the Internet of Things, and data science, with particular emphasis on healthcare applications such as medical imaging. He also contributes to postgraduate supervision as a remote co-supervisor at Lincoln University College, Malaysia. Dr. Khan has published widely in internationally recognized journals and conference proceedings and has authored several books in computer science. He is actively involved in the academic community through roles on technical program, organizing, advisory, and reviewer committees for international conferences. In addition, he holds professional certifications, has secured patents, and maintains memberships in various research organizations. His work supports interdisciplinary collaboration, particularly in computational approaches to healthcare technologies.