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ISBN 10: 3032056659 ISBN 13: 9783032056658
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Añadir al carritoPaperback. Condición: new. Paperback. This book constitutes the proceedings from the workshops BRIDGE+DeCaF 2025, held at the 28th International conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2025, which took place in Daejeon, South Korea in September 2025.The 16 papers presented in this volume were carefully reviewed and selected from the total submissions from the following workshops: First International Workshop on Bridging Regulatory Science and Medical Imaging Evaluation (BRIDGE 2025)6th MICCAI Workshop on Distributed, Collaborative and Federated Learning (DeCaF 2025) Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Añadir al carritoPaperback. Condición: new. Paperback. This book constitutes the proceedings from the workshops BRIDGE+DeCaF 2025, held at the 28th International conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2025, which took place in Daejeon, South Korea in September 2025.The 16 papers presented in this volume were carefully reviewed and selected from the total submissions from the following workshops: First International Workshop on Bridging Regulatory Science and Medical Imaging Evaluation (BRIDGE 2025)6th MICCAI Workshop on Distributed, Collaborative and Federated Learning (DeCaF 2025) Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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ISBN 10: 3032056659 ISBN 13: 9783032056658
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the proceedings from the workshops BRIDGE+DeCaF 2025, held at the 28th International conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2025, which took place in Daejeon, South Korea in September 2025.The 16 papers presented in this volume were carefully reviewed and selected from the total submissions from the following workshops: First International Workshop on Bridging Regulatory Science and Medical Imaging Evaluation (BRIDGE 2025)6th MICCAI Workshop on Distributed, Collaborative and Federated Learning (DeCaF 2025).
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Añadir al carritoPaperback. Condición: new. Paperback. This book constitutes the proceedings from the workshops BRIDGE+DeCaF 2025, held at the 28th International conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2025, which took place in Daejeon, South Korea in September 2025.The 16 papers presented in this volume were carefully reviewed and selected from the total submissions from the following workshops: First International Workshop on Bridging Regulatory Science and Medical Imaging Evaluation (BRIDGE 2025)6th MICCAI Workshop on Distributed, Collaborative and Federated Learning (DeCaF 2025) Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Añadir al carritoPaperback. Condición: New. Federated Learning for Medical Imaging: Principles, Algorithms, and Applications gives a deep understanding of the technology of federated learning (FL), the architecture of a federated system, and the algorithms for FL. It shows how FL allows multiple medical institutes to collaboratively train and use a precise machine learning (ML) model without sharing private medical data via practical implantation guidance. The book includes real-world case studies and applications of FL, demonstrating how this technology can be used to solve complex problems in medical imaging. The book also provides an understanding of the challenges and limitations of FL for medical imaging, including issues related to data and device heterogeneity, privacy concerns, synchronization and communication, etc.This book is a complete resource for computer scientists and engineers, as well as clinicians and medical care policy makers, wanting to learn about the application of federated learning to medical imaging.
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Añadir al carritoCondición: New. Presents the specific challenges in developing and deploying FL to medical imagingExplains the tools for developing or using FLPresents the state-of-the-art algorithms in the field with open source software on GithubGives .
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Añadir al carritoPaperback. Condición: New. Federated Learning for Medical Imaging: Principles, Algorithms, and Applications gives a deep understanding of the technology of federated learning (FL), the architecture of a federated system, and the algorithms for FL. It shows how FL allows multiple medical institutes to collaboratively train and use a precise machine learning (ML) model without sharing private medical data via practical implantation guidance. The book includes real-world case studies and applications of FL, demonstrating how this technology can be used to solve complex problems in medical imaging. The book also provides an understanding of the challenges and limitations of FL for medical imaging, including issues related to data and device heterogeneity, privacy concerns, synchronization and communication, etc.This book is a complete resource for computer scientists and engineers, as well as clinicians and medical care policy makers, wanting to learn about the application of federated learning to medical imaging.
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware - Federated Learning for Medical Imaging: Principles, Algorithms, and Applications gives a deep understanding of the technology of federated learning (FL), the architecture of a federated system, and the algorithms for FL. It shows how FL allows multiple medical institutes to collaboratively train and use a precise machine learning (ML) model without sharing private medical data via practical implantation guidance. The book includes real-world case studies and applications of FL, demonstrating how this technology can be used to solve complex problems in medical imaging. The book also provides an understanding of the challenges and limitations of FL for medical imaging, including issues related to data and device heterogeneity, privacy concerns, synchronization and communication, etc.This book is a complete resource for computer scientists and engineers, as well as clinicians and medical care policy makers, wanting to learn about the application of federated learning to medical imaging.
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Publicado por Springer, Berlin, Springer, 2025
ISBN 10: 3032056659 ISBN 13: 9783032056658
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the proceedings from the workshops BRIDGE+DeCaF 2025, held at the 28th International conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2025, which took place in Daejeon, South Korea in September 2025.The 16 papers presented in this volume were carefully reviewed and selected from the total submissions from the following workshops: First International Workshop on Bridging Regulatory Science and Medical Imaging Evaluation (BRIDGE 2025)6th MICCAI Workshop on Distributed, Collaborative and Federated Learning (DeCaF 2025) 166 pp. Englisch.
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book constitutes the proceedings from the workshops BRIDGE+DeCaF 2025, held at the 28th International conference onMedical Image Computing and Computer Assisted Intervention, MICCAI 2025, which took place inDaejeon, South Korea in September 2025.The 16 papers presented in this volume were carefully reviewed and selected from the total submissions from the following workshops:First International Workshop on Bridging Regulatory Science and Medical Imaging Evaluation (BRIDGE 2025)6th MICCAI Workshop on Distributed, Collaborative and Federated Learning (DeCaF 2025)Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 172 pp. Englisch.
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Publicado por Elsevier Science Publishing Co Inc, San Diego, 2025
ISBN 10: 0443236410 ISBN 13: 9780443236419
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Añadir al carritoPaperback. Condición: new. Paperback. Federated Learning for Medical Imaging: Principles, Algorithms, and Applications gives a deep understanding of the technology of federated learning (FL), the architecture of a federated system, and the algorithms for FL. It shows how FL allows multiple medical institutes to collaboratively train and use a precise machine learning (ML) model without sharing private medical data via practical implantation guidance. The book includes real-world case studies and applications of FL, demonstrating how this technology can be used to solve complex problems in medical imaging. The book also provides an understanding of the challenges and limitations of FL for medical imaging, including issues related to data and device heterogeneity, privacy concerns, synchronization and communication, etc.This book is a complete resource for computer scientists and engineers, as well as clinicians and medical care policy makers, wanting to learn about the application of federated learning to medical imaging. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.