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Published by The Institution of Engineering and Technology, 2023
ISBN 10: 1839533358 ISBN 13: 9781839533358
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Published by Institution of Engineering and Technology, GB, 2023
ISBN 10: 1839533358 ISBN 13: 9781839533358
Seller: Rarewaves USA, OSWEGO, IL, U.S.A.
Hardback. Condition: New. Machine learning algorithms are increasingly finding applications in the healthcare sector. Whether assisting a clinician to process an individual patient's data or helping administrators view hospital bed turnover, the volume and complexity of healthcare data is a compelling reason for the development of machine learning based tools to aid in its interpretation and use. This edited book focuses on the applications of machine learning in the healthcare sector, both at the macro-level for guiding policy decisions, and at the granular level, showing how ML techniques can be applied to process an individual patient's medical data to swiftly aid diagnosis. Written by an international team of experts, the book presents several applications of machine learning in the healthcare sector, including health system planning, optimisation and preparedness, outlining the benefits and challenges of coordination and data sharing. Machine learning has many applications in processing patient data and topics such as arrhythmia detection, image-guided microsurgery and early detection of Alzheimer's disease are discussed in depth. The book also looks at machine learning applications exploiting wearable sensors for real-time analysis and concepts around enhancing physical performance. Suitable for an audience of computer scientists, healthcare engineers and those involved with digital medicine, this book brings together a plethora of machine learning applications from across the board of the healthcare services.
Language: English
Published by The Institution of Engineering and Technology, 2023
ISBN 10: 1839533358 ISBN 13: 9781839533358
Seller: GreatBookPrices, Columbia, MD, U.S.A.
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Seller: Majestic Books, Hounslow, United Kingdom
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Language: English
Published by The Institution of Engineering and Technology, 2023
ISBN 10: 1839533358 ISBN 13: 9781839533358
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Published by The Institution of Engineering and Technology, 2023
ISBN 10: 1839533358 ISBN 13: 9781839533358
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Published by The Institution of Engineering and Technology, 2023
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Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Published by De Gruyter 2023-08-21, 2023
ISBN 10: 3110778785 ISBN 13: 9783110778786
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Published by Institution of Engineering and Technology, GB, 2023
ISBN 10: 1839533358 ISBN 13: 9781839533358
Seller: Rarewaves USA United, OSWEGO, IL, U.S.A.
Hardback. Condition: New. Machine learning algorithms are increasingly finding applications in the healthcare sector. Whether assisting a clinician to process an individual patient's data or helping administrators view hospital bed turnover, the volume and complexity of healthcare data is a compelling reason for the development of machine learning based tools to aid in its interpretation and use. This edited book focuses on the applications of machine learning in the healthcare sector, both at the macro-level for guiding policy decisions, and at the granular level, showing how ML techniques can be applied to process an individual patient's medical data to swiftly aid diagnosis. Written by an international team of experts, the book presents several applications of machine learning in the healthcare sector, including health system planning, optimisation and preparedness, outlining the benefits and challenges of coordination and data sharing. Machine learning has many applications in processing patient data and topics such as arrhythmia detection, image-guided microsurgery and early detection of Alzheimer's disease are discussed in depth. The book also looks at machine learning applications exploiting wearable sensors for real-time analysis and concepts around enhancing physical performance. Suitable for an audience of computer scientists, healthcare engineers and those involved with digital medicine, this book brings together a plethora of machine learning applications from across the board of the healthcare services.
Language: English
Published by Inst of Engineering & Technology, 2023
ISBN 10: 1839533358 ISBN 13: 9781839533358
Seller: Revaluation Books, Exeter, United Kingdom
Hardcover. Condition: Brand New. 1st edition. 400 pages. 9.25x6.25x1.25 inches. In Stock.
Condition: Sehr gut. Zustand: Sehr gut | Seiten: 397 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
Language: English
Published by INSTITUTION OF ENGINEERING & T, 2023
ISBN 10: 1839533358 ISBN 13: 9781839533358
Seller: moluna, Greven, Germany
Condition: New. KlappentextThis edited book focuses on the applications of machine learning in the healthcare sector, both at the macro-level for guiding policy decisions, and at the granular level, showing how machine learning techniques can be appl.
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. 1st ed. 2023 edition NO-PA16APR2015-KAP.
Seller: Books Puddle, New York, NY, U.S.A.
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Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Machine learning (ML) models, especially large pretrained deep learning (DL) models, are of high economic value and must be properly protected with regard to intellectual property rights (IPR). Model watermarking methods are proposed to embed watermarks into the target model, so that, in the event it is stolen, the model's owner can extract the pre-defined watermarks to assert ownership. Model watermarking methods adopt frequently used techniques like backdoor training, multi-task learning, decision boundary analysis etc. to generate secret conditions that constitute model watermarks or fingerprints only known to model owners. These methods have little or no effect on model performance, which makes them applicable to a wide variety of contexts. In terms of robustness, embedded watermarks must be robustly detectable against varying adversarial attacks that attempt to remove the watermarks. The efficacy of model watermarking methods is showcased in diverse applications including image classification, image generation, image captions, natural language processing and reinforcement learning. This book covers the motivations, fundamentals, techniques and protocols for protecting ML models using watermarking. Furthermore, it showcases cutting-edge work in e.g. model watermarking, signature and passport embedding and their use cases in distributed federated learning settings.
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Machine learning (ML) models, especially large pretrained deep learning (DL) models, are of high economic value and must be properly protected with regard to intellectual property rights (IPR). Model watermarking methods are proposed to embed watermarks into the target model, so that, in the event it is stolen, the model's owner can extract the pre-defined watermarks to assert ownership. Model watermarking methods adopt frequently used techniques like backdoor training, multi-task learning, decision boundary analysis etc. to generate secret conditions that constitute model watermarks or fingerprints only known to model owners. These methods have little or no effect on model performance, which makes them applicable to a wide variety of contexts. In terms of robustness, embedded watermarks must be robustly detectable against varying adversarial attacks that attempt to remove the watermarks. The efficacy of model watermarking methods is showcased in diverse applications including image classification, image generation, image captions, natural language processing and reinforcement learning. This book covers the motivations, fundamentals, techniques and protocols for protecting ML models using watermarking. Furthermore, it showcases cutting-edge work in e.g. model watermarking, signature and passport embedding and their use cases in distributed federated learning settings.
Seller: Books Puddle, New York, NY, U.S.A.
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Seller: UK BOOKS STORE, London, LONDO, United Kingdom
Condition: New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.