Machine Learning for Health Informatics - State-of-the-Art and Future Challenges (Paperback, 1st ed. 2016)

Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Lecture Notes in Computer Science, 9605
Release date:	December 2016
First published:	2016
Editors:	Andreas Holzinger
Dimensions:	235 x 155 x 26mm (L x W x T)
Format:	Paperback
Pages:	481
Edition:	1st ed. 2016
ISBN-13:	978-3-319-50477-3
Categories:	Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Computing & IT > Social & legal aspects of computing > Health & safety aspects of computing Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Books > Computing & IT > Applications of computing > Image processing > General Promotions
LSN:	3-319-50477-0
Barcode:	9783319504773

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