Machine Learning for Healthcare Technologies - Rilegato

Rilegato

ISBN 10: 1849199787 ISBN 13: 9781849199780

Casa editrice: Inst of Engineering & Technology, 2016

Riassunto

This book brings together chapters on the state-of-the-art in machine learning (ML) as it applies to the development of patient-centred technologies, with a special emphasis on “big data” and mobile data. With contributions from international experts from prestigious institutions it describes cutting edge research and makes accessible, for the first time, the latest in Bayesian non-parametrics for healthcare. This is one of the key frontiers in ML, and its application to healthcare will serve as a useful tutorial guide for both ML-focused and biomedical engineers. There are very few books that are accessible in this key area of ML, and absolutely none on the use of such technologies for mobile healthcare – despite a substantial amount of research that has taken place in this field at key biomedical and clinical sites across the world.

Topics covered include an introduction to machine learning in healthcare; discovering trends in patient physiology; Bayesian time-series analysis for patient monitoring; mobile healthcare for the developing world; massively-multiscale machine learning for healthcare; time-series clustering for understanding patient data; machine learning for home healthcare; fusing genomics and healthcare data; machine learning for mental health; mobile healthcare with analysis-on-a-chip; Bayesian analytics for medical data fusion.

This is an important book for academic and industrial researchers working in healthcare technologies, biomedical engineering and machine learning. It will also be of interest to advanced students working in these areas and commercial developers of computing-based healthcare applications.

Su questo libro

L'autore

David Clifton is Associate Professor of Engineering Science at the University of Oxford, and a Research Fellow of the Royal Academy of Engineering. He leads the Computational Health Informatics Laboratory at the Institute of Biomedical Engineering in Oxford's Department of Engineering Science. Prof. Clifton's research focuses on the development of 'big data' machine learning for tracking the health of complex systems. He previously worked on the world's first FDA-approved multivariate patient monitoring system, and systems that are used to monitor 20,000 patients each month in the UK National Health Service.

Dettagli dell'edizione

• Editore: Inst of Engineering & Technology
• Data di pubblicazione: 2016
• Lingua: Inglese
• ISBN 10: 1849199787
• ISBN 13: 9781849199780
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 303
• Redattore: Clifton David A.
• Contatto del produttore: non disponibile
• Persona responsabile: GPSR Kontakt; gpsr@libri.de; ; Friedensallee 273; Hamburg; 22763; Germania