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Machine Learning for Healthcare Technologies

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서명/저자사항Machine Learning for Healthcare Technologies.
개인저자Clifton, David A.
발행사항The Institution of Engineering and Technology, 2016.
형태사항1 online resource (296 pages).
총서사항Healthcare technologies;2
기타형태 저록Print version: Clifton, David A. Machine Learning for Healthcare Technologies. The Institution of Engineering and Technology, 2016 9781849199780 1849199787
ISBN1849199795
9781849199797


내용주기1. Machine learning for healthcare technologies -- an introduction / David A. Clifton; 2. Detecting artifactual events in vital signs monitoring data / Partha Lal, Christopher K.I. Williams, Konstantinos Georgatzis, Christopher Hawthorne, Paul McMonagle, Ian Piper and Martin Shaw; 3. Signal processing and feature selection preprocessing for classification in noisy healthcare data / Qiao Li, Chengyu Liu, Julien Oster and Gari D. Clifford; 4. ECG model-based Bayesian filtering / Julien Oster.
5. The power of tensor decompositions in biomedical applications / Borb?la Hunyadi, Sabine Van Huffel and Maarten De Vos6. Patient physiological monitoring with machine learning / Marco A.F. Pimentel and David A. Clifton; 7. A Bayesian model for fusing biomedical labels / Tingting Zhu, Gari D. Clifford and David A. Clifton; 8. Incorporating end-user preferences in predictive models / Suchi Saria and Daniel P. Robinson; 9. Variational Bayesian non-parametric inference for infectious disease models / James Hensman and Theodore Kypraios.
10. Predicting antibiotic resistance from genomic data / Yang Yang, Katherine E. Niehaus and David A. Clifton11. Machine learning for chronic disease / Katherine E. Niehaus and David A. Clifton; 12. Big data and optimisation of treatment strategies / Shamim Nemati and Mohammad M. Ghassemi; 13. Decision support systems for home monitoring applications: Classification of activities of daily living and epileptic seizures / Stijn Luca, Lode Vuegen, Hugo Van hamme, Peter Karsmakers and Bart Vanrumste; Index.
요약This 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.
일반주제명Medical innovations.
Medical informatics.
Machine learning.
Medicine --Data processing.
HEALTH & FITNESS --Holism.
HEALTH & FITNESS --Reference.
MEDICAL --Alternative Medicine.
MEDICAL --Atlases.
MEDICAL --Essays.
MEDICAL --Family & General Practice.
MEDICAL --Holistic Medicine.
MEDICAL --Osteopathy.
Machine learning.
Medical informatics.
Medical innovations.
Medicine --Data processing.
Bayes methods.
health care.
learning (artificial intelligence)
patient monitoring.
physiological models.
Biomedical Technology.
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