Machine Learning in Clinical Neuroscience:Foundations and Applications (Acta Neurochirurgica Supplement, 134) 1st ed. 2022 Edition
Author:Victor E. Staartjes,Luca Regli,Carlo Serra (Editor)
Publisher Finelybook 出版社：Springer; 1st ed. 2022 edition (December 4, 2021)
pages 页数：368 pages
This book bridges the gap between data scientists and clinicians Author:introducing all relevant aspects of machine learning in an accessible way, and will certainly foster new and serendipitous applications of machine learning in the clinical neurosciences. Building from the ground up Author:communicating the foundational knowledge and intuitions first before progressing to more advanced and specific topics, the book is well-suited even for clinicians without prior machine learning experience.
Authored Author:a wide array of experienced global machine learning groups, the book is aimed at clinicians who are interested in mastering the basics of machine learning and who wish to get started with their own machine learning research.
The volume is structured in two major parts:The first uniquely introduces all major concepts in clinical machine learning from the ground up, and includes step-Author:-step instructions on how to correctly develop and validate clinical prediction models. It also includes methodological and conceptual foundations of other applications of machine learning in clinical neuroscience, such as applications of machine learning to neuroimaging, natural language processing, and time series analysis. The second part provides an overview of some state-of-the-art applications of these methodologies.
The Machine Intelligence in Clinical Neuroscience (MICN) Laboratory at the Department of Neurosurgery of the University Hospital Zurich studies clinical applications of machine intelligence to improve patient care in clinical neuroscience. The group focuses on diagnostic, prognostic and predictive analytics that aid in decision-making Author:increasing objectivity and transparency to patients. Other major interests of our group members are in medical imaging, and intraoperative applications of machine vision.