Machine Learning in Clinical Neuroscience: Foundations and Applications (Acta Neurochirurgica Supplement, 134) - Hardcover

Hardcover

ISBN 10: 3030852911 ISBN 13: 9783030852917

Publisher: Springer, 2021

Synopsis

This book bridges the gap between data scientists and clinicians by 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 by 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 by 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-by-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 by increasing objectivity and transparency to patients. Other major interests of our group members are in medical imaging, and intraoperative applications of machine vision.

About this title

About the Author

Victor E. Staartjes:
Dr. Victor Staartjes is the group leader of the Machine Intelligence in Clinical Neuroscience (MICN) Laboratory and a neurosurgery resident at the University Hospital Zurich under Prof. L. Regli. Originating from Amsterdam, he received his medical degree from the University of Zurich and is studying for a PhD in clinical machine learning at the Vrije Universiteit Amsterdam. Dr. Staartjes' research interests are in applications of machine learning to medical imaging and clinical prediction modeling, as well as robotic neurosurgery and personalized / precision medicine.

Luca Regli:
Prof. Luca Regli studied medicine at the University of Lausanne, he trained with Nicolas de Tribolet and obtained board certification in neurosurgery. At the renowned Mayo Clinic in Rochester, USA he specialized in the microsurgical treatment of complex intracranial lesions. In 2008 he was called as a full professor and chairman of neurosurgery at the University Medical Center of Utrecht, the Netherlands. In 2012 the University of Zurich nominated him as full professor and the University Hospital Zurich invited him to chair the Department of Neurosurgery, following into the steps of famous predecessors of Prof. Krayenbuehl, Prof. Yaşargil, Prof. Yonekawa, and Prof. Bertalanffy, which is a renowned international reference center for cerebrovascular diseases, neuro-oncology and functional neurosurgery. Prof. Regli has developed his research interests driven by clinical questions in the domain of cerebral ischemia, cerebral metabolism, cerebral homeostasis and edema as well as in cutting-edge surgical techniques for cerebral revascularization and intra-operative imaging. The academic activity is reflected in over 265 publications in peer reviewed journals and 18 chapters in textbooks. As one of the worldwide leading experts in neurosurgery he is regularly invited as speaker at meetings all over the world. The clinical expertise is reflected in the daily management of patients with cerebrovascular lesions as well as brain tumors. He has personally treated microsurgically more than 1000 patients with cerebral aneurysms. As a recognized leading expert for management of vascular lesions he regularly gets referrals of patients with complex vascular lesions.

Carlo Serra
Dr. Carlo Serra is an assistant professor of neurosurgery and senior neurosurgeon at the University Hospital Zurich and co-leads the MICN Laboratory. Originating from Venice, Dr. Serra completed his medical studies and part of residency in Milan. He then moved to Zurich where he trained with Prof. L. Regli. During a fellowship with Prof. U. Türe and Prof. M.G. Yaşargil in Istanbul, he developed a special expertise in brain tumor and skull base surgery as well as microneurosurgical anatomy, specifically white matter fiber dissection. He is currently responsible for the neuro-oncology and skull base programs of the Department of Neurosurgery of the University Hospital Zurich.

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From the Back Cover

This book bridges the gap between data scientists and clinicians by 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 by 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 by 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-by-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 by increasing objectivity and transparency to patients. Other major interests of our group members are in medical imaging, and intraoperative applications of machine vision.

Edition details

• Publisher: Springer
• Publication date: 2021
• Language: English
• ISBN 10: 3030852911
• ISBN 13: 9783030852917
• Binding: Hardcover
• Edition number: 1
• Number of pages: 368
• Editor: Staartjes Victor E., Regli Luca, Serra Carlo