Artificial Intelligence in Neurosurgery

Translatable Technologies and Current Advances
1. Auflage 2026
ISBN: 978-1-032-74838-2
Verlag: Taylor & Francis Ltd

Buch, Englisch, 280 Seiten, Format (B × H): 178 mm x 254 mm

Reihe: AI in Clinical Practice

The field of neurosurgery stands at the precipice of a transformative era, driven by the rapid evolution of artificial intelligence (AI). From optimizing patient selection and surgical parameters to enhancing intraoperative precision, AI has already begun to reshape the landscape of neurosurgical care. Yet, as these technologies advance from preclinical studies to real-world applications, the challenges of responsible integration, evaluation, and safety have become increasingly urgent.

This groundbreaking textbook equips neurosurgeons with the foundational knowledge to navigate the complexities of AI in clinical practice. It explores the remarkable progress of AI systems, from machine learning–enhanced neuronavigation to agentic systems capable of autonomous, multi-step workflows. With a focus on real-world clinical data, fairness, and interpretability, the book addresses the critical hurdles of evaluation lag, dataset curation, and regulatory oversight.

As AI transitions from passive tools to active participants in medical problem-solving, this text provides a roadmap for neurosurgeons to lead the charge in developing, implementing, and critically assessing these transformative technologies. By bridging the gap between innovation and practice, this book ensures that the next generation of neurosurgeons is prepared to harness the full potential of AI while safeguarding patient care.

Zielgruppe

Professional Practice & Development

Autoren/Hrsg.

Veeravagu, Anand

Schonfeld, Ethan

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Chirurgie Onkologische Chirurgie
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Chirurgie Neurochirurgie
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Chirurgie Plastische, Rekonstruktive & Kosmetische Chirurgie

Inhaltsverzeichnis

Chapter 1: Neurons to Networks – Introducing the Role of Artificial Intelligence in Modern Neurosurgery  Chapter 2: Multimodal Foundation Models for Healthcare  Chapter 3: From Data to Decisions: AI-Driven Outcome Prediction in Spine Surgery  Chapter 4: Outcome Prediction in Brain Surgery  Chapter 5: Outcome Prediction in Neurosurgery: Liquid Biopsy and the Role of Machine Learning  Chapter 6: Diagnostic Applications of Artificial Intelligence in Neuro Oncology  Chapter 7: Detection and Diagnosis of Cerebrovascular Lesions Using Artificial Intelligence  Chapter 8: Artificial Intelligence Usage by Robotics in Neurosurgery  Chapter 9: The Compass of the Future: Machine Learning-Guided Navigation in Spine Surgery  Chapter 10: Artificial Intelligence for Surgical Workflow Analysis  Chapter 11: The Mind-Machine Interface  Chapter 12: Neurosurgical Sub-Task Automation  Chapter 13: Artificial Intelligence for Simulation and Neurosurgical Training  Chapter 14: Computer Vision in Neurosurgery  Chapter 15: Large Language Models in Neurosurgery  Chapter 16: Federated Learning in Neurosurgery  Chapter 17: Policy Perspective on the Regulatory Landscape, Evaluation, and Translation of Artificial Intelligence for Neurosurgery  Chapter 18: Neurosurgical Data Sources and Data Needs for Artificial Intelligence  Chapter 19: Current Challenges for Deep Learning Neurosurgery: Clinically Applicable Metrics and Domain Shift  Chapter 20: Using Operating Room Audio and Video for Predictive Analytics  Chapter 21: Advancing Basic Laboratory Research by Artificial Intelligence

Über Autor(innen)

Anand Veeravagu, Associate Professor of Neurosurgery Department of Neurosurgery Stanford University School of Medicine

Dr. Veeravagu is an expert in the field of minimally invasive spine surgery and serves on national committees. He is the Director of Minimally Invasive Spine Surgery at Stanford University and Director of the Stanford Neurosurgical Artificial Intelligence and Machine Learning Laboratory. He currently serves as the team neurosurgery for the San Francisco 49ers. He is a leader in the field, having edited and authored a textbook on Robotic and Navigated Spine Surgery.

Ethan Schonfeld is a medical student at Stanford University School of Medicine. He is a member of the Stanford Neurosurgical Artificial Intelligence and Machine Learning Laboratory. He has earned a master's degree at Stanford Medicine in Biomedical Informatics where his research was focused on the generation of synthetic imaging in neurosurgery. He has authored numerous journal articles and multiple textbook chapters on artificial intelligence in neurosurgery.