Medical Robotics and Computer Assisted Surgery

Aim & scope

Medical Robotics and Computer Assisted Surgery: AI-enhanced, Data-driven, and Evidence-based Approaches series presents a comprehensive suite of reference books containing foundational knowledge on the human-surgical robot interface, presenting researchers, scientists, clinicians, and students with practical and up-to-date resources on the application and integration of computational techniques into robots for the treatment and diagnosis of human disease.

This book series will contain volumes presenting major aspects of the complex range of modern healthcare techniques and technologies utilizing robots that are used to diagnose, monitor, and treat diseases or medical conditions affecting humans. Volumes will cover topics on medical robotics and intelligent healthcare technologies; automation for surgery; surgical navigation and augmented reality systems; robotic process automation (RPA) in healthcare; machine learning and cognitive surgical robotics; bio-inspired robotics and bio mimics; emerging, multi-specialty applications of robotic technologies; and robot structure design and control, amongst others.

Image Cover for Medical Robotics and Computer Assisted Surgery

The book series will not only emphasize traditional computational techniques but will discuss AI, deep learning, and machine learning in the robotics field with broad coverage of basic scientific applications. This series will be suitable for a wide range of readers from biomedical engineering, mechanical engineering, electrical engineering, computer science, and medicine who are developing robotic systems and computer-assisted tools used in surgical procedures and medical interventions.

Audience

Researchers, scientists, professionals, graduate students, and experts working in robotics -biomedical engineering, computer science, control engineering, mechanical engineering, electrical engineering, healthcare IoT, computational intelligence, machine learning, medical image processing, medical informatics, clinical big data analytics.