
Machine Learning for Healthcare Technologies by David A Clifton
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.-
Handbook of Cybersecurity for e-Health
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Enhanced Living Environments
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Health Informatics
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Introduction to Biomechatronics
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Biomedical Nanomaterials
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Applications of Artificial Intelligence in E-Healthcare Systems
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Human Monitoring, Smart Health and Assisted Living
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Medical Information Processing and Security
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Blockchain Technology in e-Healthcare Management
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Wearable Technologies and Wireless Body Sensor Networks for Healthcare
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Exploring Intelligent Healthcare with Quantum Computing
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Wireless Medical Sensor Networks for IoT-based eHealth
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Security and Privacy of Electronic Healthcare Records
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Control of Prosthetic Hands
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Advances in Telemedicine for Health Monitoring
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Value-based Learning Healthcare Systems
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Neurotechnology
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Blockchain and Machine Learning for e-Healthcare Systems
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Soft Robots for Healthcare Applications
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Portable Biosensors and Point-of-Care Systems
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Semiconductor Lasers and Diode-based Light Sources for Biophotonics
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Patient-Centered Digital Healthcare Technology
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Handbook of Speckle Filtering and Tracking in Cardiovascular Ultrasound Imaging and Video
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Secure Big-data Analytics for Emerging Healthcare in 5G and Beyond
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Explainable Artificial Intelligence in Medical Decision Support Systems
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Evolving Predictive Analytics in Healthcare
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Applications of Machine Learning in Digital Healthcare
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Active and Assisted Living
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Engineering High Quality Medical Software
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AI, Numerical Optimization, IoT and Blockchain for Healthcare 4.0
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Artificial Intelligence and Blockchain Technology in Modern Telehealth Systems
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Energy Harvesting Solutions for Implantable Medical Devices
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The Internet of Medical Things
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Techniques and Technologies in Electrical Stimulation for Neuromuscular Rehabilitation
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Medical Equipment Engineering
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Innovations in Healthcare Informatics
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Blockchain for 5G Healthcare Applications
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Technologies and Techniques in Gait Analysis
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Digital Methods and Tools to Support Healthy Ageing
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Smart Health Technologies for the COVID-19 Pandemic
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Mobile Technologies for Delivering Healthcare in Remote, Rural or Developing Regions
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Technologies for Healthcare 4.0
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Digital Twin Technologies for Healthcare 4.0
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Technology-Enabled Motion Sensing and Activity Tracking for Rehabilitation
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Cybersecurity in Emerging Healthcare Systems
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Deep Learning in Medical Image Processing and Analysis
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Medical Imaging Informatics
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.
| SKU | Unavailable |
| ISBN 13 | 9781849199780 |
| ISBN 10 | 1849199787 |
| Title | Machine Learning for Healthcare Technologies |
| Author | David A Clifton |
| Series | Healthcare Technologies |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Institution of Engineering and Technology |
| Year published | 2016-10-28 |
| Number of pages | 320 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |














































