Machine Learning in Clinical Neuroscience

Machine Learning in Clinical Neuroscience
Author :
Publisher : Springer Nature
Total Pages : 343
Release :
ISBN-10 : 9783030852924
ISBN-13 : 303085292X
Rating : 4/5 (92X Downloads)

Book Synopsis Machine Learning in Clinical Neuroscience by : Victor E. Staartjes

Download or read book Machine Learning in Clinical Neuroscience written by Victor E. Staartjes and published by Springer Nature. This book was released on 2021-12-03 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Machine Learning in Clinical Neuroscience Related Books

Machine Learning in Clinical Neuroimaging
Language: en
Pages: 185
Authors: Ahmed Abdulkadir
Categories: Computers
Type: BOOK - Published: 2021-09-22 - Publisher: Springer Nature

GET EBOOK

This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2021, held on September 27,
Machine Learning in Clinical Neuroscience
Language: en
Pages: 343
Authors: Victor E. Staartjes
Categories: Medical
Type: BOOK - Published: 2021-12-03 - Publisher: Springer Nature

GET EBOOK

This book bridges the gap between data scientists and clinicians by introducing all relevant aspects of machine learning in an accessible way, and will certainl
Machine Learning
Language: en
Pages: 412
Authors: Andrea Mechelli
Categories: Medical
Type: BOOK - Published: 2019-11-14 - Publisher: Academic Press

GET EBOOK

Machine Learning is an area of artificial intelligence involving the development of algorithms to discover trends and patterns in existing data; this informatio
Big Data in Psychiatry and Neurology
Language: en
Pages: 386
Authors: Ahmed Moustafa
Categories: Medical
Type: BOOK - Published: 2021-06-11 - Publisher: Academic Press

GET EBOOK

Big Data in Psychiatry and Neurology provides an up-to-date overview of achievements in the field of big data in Psychiatry and Medicine, including applications
The Cambridge Handbook of Research Methods in Clinical Psychology
Language: en
Pages: 600
Authors: Aidan G. C. Wright
Categories: Psychology
Type: BOOK - Published: 2020-03-31 - Publisher: Cambridge University Press

GET EBOOK

This book integrates philosophy of science, data acquisition methods, and statistical modeling techniques to present readers with a forward-thinking perspective