Machine Learning for Healthcare Technologies

Herausgeber: Clifton, David A

• Gebundenes Buch

Produktbeschreibung

This book provides a snapshot of the state of current research at the interface between machine learning and healthcare with special emphasis on machine learning projects that are (or are close to) achieving improvement in patient outcomes.

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Produktdetails

• Verlag: Institution of Engineering & Technology
• Seitenzahl: 320
• Erscheinungstermin: 28. Oktober 2016
• Englisch
• Abmessung: 239mm x 163mm x 20mm
• Gewicht: 590g
• ISBN-13: 9781849199780
• ISBN-10: 1849199787
• Artikelnr.: 45060541

Inhaltsangabe

* Chapter 1: Machine learning for healthcare technologies - an
introduction
* Chapter 2: Detecting artifactual events in vital signs monitoring
data
* Chapter 3: Signal processing and feature selection preprocessing for
classification in noisy healthcare data
* Chapter 4: ECG model-based Bayesian filtering
* Chapter 5: The power of tensor decompositions in biomedical
applications
* Chapter 6: Patient physiological monitoring with machine learning
* Chapter 7: A Bayesian model for fusing biomedical labels
* Chapter 8: Incorporating end-user preferences in predictive models
* Chapter 9: Variational Bayesian non-parametric inference for
infectious disease models
* Chapter 10: Predicting antibiotic resistance from genomic data
* Chapter 11: Machine learning for chronic disease
* Chapter 12: Big data and optimisation of treatment strategies
* Chapter 13: Decision support systems for home monitoring
applications: Classification of activities of daily living and
epileptic seizures