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Sprache: Englisch
Verlag: The Institution of Engineering a, 2024
ISBN 10: 1839537434 ISBN 13: 9781839537431
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Taschenbuch. Zustand: Neu. Machine Learning and Analytics in Healthcare Systems | Principles and Applications | Himani Bansal (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | CRC Press | EAN 9780367564865 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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In den WarenkorbZustand: New. pp. 372.
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Sprache: Englisch
Verlag: Wiley-Scrivener (edition 1), 2022
ISBN 10: 1119791790 ISBN 13: 9781119791799
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In den WarenkorbPaperback. Zustand: Brand New. 220 pages. 9.25x7.50x9.25 inches. In Stock.
Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 484 | Sprache: Englisch | Produktart: Bücher | This book provides a hands-on introduction to Machine Learning (ML) from a multidisciplinary perspective that does not require a background in data science or computer science. It explains ML using simple language and a straightforward approach guided by real-world examples in areas such as health informatics, information technology, and business analytics. The book will help readers understand the various key algorithms, major software tools, and their applications. Moreover, through examples from the healthcare and business analytics fields, it demonstrates how and when ML can help them make better decisions in their disciplines.The book is chiefly intended for undergraduate and graduate students who are taking an introductory course in machine learning. It will also benefit data analysts and anyone interested in learning ML approaches.
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In den WarenkorbHardcover. Zustand: Brand New. 152 pages. 10.00x7.00x0.44 inches. In Stock.
Sprache: Englisch
Verlag: Springer International Publishing, Springer Nature Switzerland, 2022
ISBN 10: 3031169891 ISBN 13: 9783031169892
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a hands-on introduction to Machine Learning (ML) from a multidisciplinary perspectivethat does not requirea background in data science or computer science. It explains ML using simple language and a straightforward approach guided by real-world examples in areas such as health informatics, information technology, and business analytics.The book will help readers understand the various key algorithms, major software tools, and their applications. Moreover, through examples from the healthcare and business analytics fields, it demonstrates how and when ML can help them make better decisions in their disciplines.The book is chiefly intended for undergraduate and graduate students who are taking an introductory course in machine learning. It will also benefit data analysts and anyone interested in learning ML approaches.
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In den WarenkorbHardcover. Zustand: Brand New. 465 pages. 9.50x6.25x1.25 inches. In Stock.
Sprache: Englisch
Verlag: Springer International Publishing, Springer International Publishing, 2023
ISBN 10: 3031111567 ISBN 13: 9783031111563
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Artificial intelligence (AI) and machine learning (ML) have transformed many standard and conventional methods in undertaking health and well-being issues of humans. AL/ML-based systems and tools play a critical role in this digital and big data era to address a variety of medical and healthcare problems,improving treatments and quality of care for patients.This edition on AI and ML for healthcare consists of two volumes. The first presents selected AI and ML studies on medical imaging and healthcare data analytics, while the second unveils emerging methodologies and trends in AI and ML for delivering better medical treatments and healthcare services in the future.In this first volume, progresses in AI and ML technologies for medical image, video, and signal processing as well as health information and data analytics are presented. These selected studies offer readers theoretical and practical knowledge and ideas pertaining to recent advances in AI and ML for effective and efficient image and data analytics, leading to state-of-the-art AI and ML technologies for advancing the healthcare sector.