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Artificial Intelligence in Neurosurgery: Translatable Technologies and Current Advances: AI in Clinical Practice

Editat de Anand Veeravagu, Ethan Schonfeld
en Limba Engleză Paperback – 5 oct 2026
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.
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Specificații

ISBN-13: 9781032748375
ISBN-10: 1032748370
Pagini: 280
Ilustrații: 60
Dimensiuni: 178 x 254 mm
Ediția:1
Editura: CRC Press
Colecția CRC Press
Seria AI in Clinical Practice


Public țintă

Professional Practice & Development

Cuprins

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

Notă biografică

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. 

Descriere

This groundbreaking text equips neurosurgeons with the foundational knowledge to navigate the complexities of AI in clinical practice. 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.