Published by Springer, 2024
ISBN 10: 3031393546 ISBN 13: 9783031393549
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Published by Springer, 2024
ISBN 10: 3031393546 ISBN 13: 9783031393549
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Condition: Fine. Book is in Used-LikeNew condition. Pages and cover are clean and intact. Used items may not include supplementary materials such as CDs or access codes. May show signs of minor shelf wear. 3.77.
Published by Springer, 2024
ISBN 10: 3031393546 ISBN 13: 9783031393549
Seller: GreatBookPrices, Columbia, MD, U.S.A.
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Published by Springer International Publishing AG, 2024
ISBN 10: 3031393546 ISBN 13: 9783031393549
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Published by Springer, 2024
ISBN 10: 3031393546 ISBN 13: 9783031393549
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Published by Springer, 2024
ISBN 10: 3031393546 ISBN 13: 9783031393549
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Published by Springer, 2024
ISBN 10: 3031393546 ISBN 13: 9783031393549
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Published by Springer, 2024
ISBN 10: 3031393546 ISBN 13: 9783031393549
Seller: GreatBookPricesUK, Castle Donington, DERBY, United Kingdom
Condition: As New. Unread book in perfect condition.
Published by Springer Nature, 2024
ISBN 10: 3031393546 ISBN 13: 9783031393549
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Hardcover. Condition: Brand New. 1st edition. 810 pages. 9.25x6.25x2.00 inches. In Stock.
Published by Springer International Publishing AG, 2024
ISBN 10: 3031393546 ISBN 13: 9783031393549
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Published by Springer, 2024
ISBN 10: 3031393546 ISBN 13: 9783031393549
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Published by Springer, Berlin, Springer International Publishing, Institute For Health Informatics, Springer Nov 2023, 2023
ISBN 10: 3031393546 ISBN 13: 9783031393549
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Buch. Condition: Neu. Neuware - This open access book provides a detailed review of the latest methods and applications of artificial intelligence (AI) and machine learning (ML) in medicine. With chapters focusing on enabling the reader to develop a thorough understanding of the key concepts in these subject areas along with a range of methods and resulting models that can be utilized to solve healthcare problems, the use of causal and predictive models are comprehensively discussed. Care is taken to systematically describe the concepts to facilitate the reader in developing a thorough conceptual understanding of how different methods and resulting models function and how these relate to their applicability to various issues in health care and medical sciences. Guidance is also given on how to avoid pitfalls that can be encountered on a day-to-day basis and stratify potential clinical risks. Artificial Intelligence and Machine Learning in Health Care and Medical Sciences: Best Practices and Pitfallsis a comprehensive guide to how AI and ML techniques can best be applied in health care. The emphasis placed on how to avoid a variety of pitfalls that can be encountered makes it an indispensable guide for all medical informatics professionals and physicians who utilize these methodologies on a day-to-day basis. Furthermore, this work will be of significant interest to health data scientists, administrators and to students in the health sciences seeking an up-to-date resource on the topic.
Published by Springer, 2024
ISBN 10: 3031393546 ISBN 13: 9783031393549
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Published by Springer International Publishing, 2024
ISBN 10: 3031393546 ISBN 13: 9783031393549
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Gebunden. Condition: New. Covers how to build models that can be applied with minimal risk in high-stakes settingsDiscusses how to integrate clinical and molecular analysis and modelling in medicine and healthcareFeatures detailed insight into both predictive and ca.
Published by Springer Nature, 2024
ISBN 10: 3031393546 ISBN 13: 9783031393549
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Published by Springer Nature, 2024
ISBN 10: 3031393546 ISBN 13: 9783031393549
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