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In den WarenkorbPaperback. Zustand: Brand New. 143 pages. 9.26x6.11x0.31 inches. In Stock.
Sprache: Englisch
Verlag: Springer, Berlin|Springer Nature Switzerland|Springer, 2024
ISBN 10: 3031543025 ISBN 13: 9783031543029
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In den WarenkorbZustand: New. Utku Kose is an Associate Professor in Suleyman Demirel University, Turkey, and Visiting Researcher in University of North Dakota, USA. His research interests include artificial intelligence, machine ethics, artificial intelligence safety, biomedi.
Sprache: Englisch
Verlag: Springer Nature Switzerland AG, 2026
ISBN 10: 3032215137 ISBN 13: 9783032215130
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the proceedings of the 4th International Workshop on Explainable Artificial Intelligence in Healthcare, XAI-Healthcare 2025, and the Second International Workshop on Process Mining Applications for Healthcare, PM4H 2025, held in Pavia, Italy, during June 26, 2025.The 14 full papers were included in this were carefully reviewed and selected from 27 submissions. They focus on Machine Learning, Decision Support Systems, Natural Language, Human-Computer Interaction, and Healthcare sciences.
Sprache: Englisch
Verlag: Springer Nature Switzerland AG, 2026
ISBN 10: 3032215137 ISBN 13: 9783032215130
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Taschenbuch. Zustand: Neu. Explainable Artificial Intelligence and Process Mining Applications for Healthcare | 4th International Workshop, XAI-Healthcare 2025, and 2nd International Workshop, PM4H 2025, Pavia, Italy, June 26, 2025, Proceedings | Carlos Fernandez-Llatas (u. a.) | Taschenbuch | Communications in Computer and Information Science | xii | Englisch | 2026 | Springer Nature Switzerland AG | EAN 9783032215130 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Taschenbuch. Zustand: Neu. Explainable Artificial Intelligence and Process Mining Applications for Healthcare | Third International Workshop, XAI-Healthcare 2023, and First International Workshop, PM4H 2023, Portoroz, Slovenia, June 15, 2023, Proceedings | Jose M. Juarez (u. a.) | Taschenbuch | Communications in Computer and Information Science | xii | Englisch | 2024 | Springer | EAN 9783031543029 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the proceedings of theThird International Workshop on Explainable Artificial Intelligence in Healthcare, XAI-Healthcare 2023, and the First International Workshop on Process Mining Applications for Healthcare, PM4H 2023, which took place in conjunction with AIME 2023 inPortoroz, Slovenia, on June 15, 2023.The 7 full papers included from XAI-Healthcare were carefully reviewed and selected from 11 submissions. They focus on all aspects of eXplainable Artificial Intelligence (XAI) in the medical and healthcare field. For PM4H 5 papers have been accepted from 17 submissions. They deal with data-driven process analysis techniques in healthcare.
Sprache: Englisch
Verlag: Taylor & Francis Ltd (Sales) Jun 2026, 2026
ISBN 10: 1032546670 ISBN 13: 9781032546674
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Taschenbuch. Zustand: Neu. Neuware - This book highlights the use of explainable artificial intelligence (XAI) for healthcare problems, in order to improve trustworthiness, performance and sustainability levels in the context of applications.Explainable Artificial Intelligence (XAI) in Healthcare adopts the understanding that AI solutions should not only have high accuracy performance, but also be transparent, understandable and reliable from the end user's perspective. The book discusses the techniques, frameworks, and tools to effectively implement XAI methodologies in critical problems of healthcare field. The authors offer different types of solutions, evaluation methods and metrics for XAI and reveal how the concept of explainability finds a response in target problem coverage. The authors examine the use of XAI in disease diagnosis, medical imaging, health tourism, precision medicine and even drug discovery. They also point out the importance of user perspectives and value of the data used in target problems. Finally, the authors also ensure a well-defined future perspective for advancing XAI in terms of healthcare.This book will offer great benefits to students at the undergraduate and graduate levels and researchers. The book will also be useful for industry professionals and clinicians who perform critical decision-making tasks.
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Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book constitutes the proceedings of the Third International Workshop on Explainable Artificial Intelligence in Healthcare, XAI-Healthcare 2023, and the First International Workshop on Process Mining Applications for Healthcare, PM4H 2023, which took place in conjunction with AIME 2023 in Portoroz, Slovenia, on June 15, 2023.The 7 full papers included from XAI-Healthcare were carefully reviewed and selected from 11 submissions. They focus on all aspects of eXplainable Artificial Intelligence (XAI) in the medical and healthcare field. For PM4H 5 papers have been accepted from 17 submissions. They deal with data-driven process analysis techniques in healthcare.
Sprache: Englisch
Verlag: The Institution of Engineering and Technology, 2023
ISBN 10: 1839536209 ISBN 13: 9781839536205
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In den WarenkorbPaperback. Zustand: Brand New. 320 pages. 9.25x7.50x0.67 inches. In Stock.
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In den WarenkorbHardcover. Zustand: Brand New. 256 pages. 9.19x6.13x9.21 inches. In Stock.
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In den WarenkorbZustand: New. 2025. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.
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In den WarenkorbZustand: New. 2025. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.
Sprache: Englisch
Verlag: Elsevier Science Publishing Co Inc Mai 2025, 2025
ISBN 10: 0443239797 ISBN 13: 9780443239793
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Taschenbuch. Zustand: Neu. Neuware - In an era where Artificial Intelligence (AI) is revolutionizing healthcare, Explainable AI in Healthcare Imaging for Precision Medicine addresses the critical need for transparency, trust, and accountability in AI-driven medical technologies. As AI becomes an integral part of clinical decision-making, especially in imaging and precision medicine, the question of how AI reaches its conclusions grows increasingly significant. This book explores how Explainable AI (XAI) is transforming healthcare by making AI systems more interpretable, reliable, and transparent, empowering clinicians and enhancing patient outcomes.Through a comprehensive examination of the latest research, real-world case studies, and expert insights, this book delves into the application of XAI in medical imaging, disease diagnosis, treatment planning, and personalized care. It discusses the technical methodologies behind XAI, the challenges and opportunities of its integration into healthcare, and the ethical and regulatory considerations that will shape the future of AI-assisted medical decisions.Key areas of focus include the role of XAI in improving diagnostic accuracy in fields such as radiology, pathology, and genomics and its potential to enhance collaboration between AI systems, healthcare professionals, and patients. The book also highlights practical applications of XAI in personalized medicine, showing how explainable models help tailor treatments to individual patients, and discusses how XAI can contribute to reducing bias and improving fairness in medical decision-making.Written by leading experts in AI, healthcare, and precision medicine, Explain[S3G1] able AI in Healthcare Imaging for Precision Medicine is an essential resource for researchers, clinicians, students, and policymakers. Whether you are looking to stay at the forefront of AI innovations in healthcare or seeking to understand how explainability can build trust in AI systems, this book provides the insights and knowledge needed to navigate the evolving landscape of AI in medicine. It invites readers to explore how XAI can revolutionize healthcare and precision medicine, shaping a future where AI is both powerful and trustworthy.