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The 16 full papers presented in this book were carefully reviewed and selected from 32 submissions. They discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains.
Lecture Notes in Computer Science: 5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings
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Lecture Notes in Computer Science: 5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings
Koch, Lisa; Cardoso, M. Jorge; Ferrante, Enzo; Kamnitsas, Konstantinos; Islam, Mobarakol; Jiang, Meirui; Rieke, Nicola; Tsaftaris, Sotirios A.; Yang, Dong
This book constitutes the refereed proceedings of the 5th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2023, which was held in conjunction with MICCAI 2023, in October 2023.
The 16 full papers presented in this book were carefully reviewed and selected from 32 submissions. They discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains.
Details
Published by: Springer
Publication Date: 2023-10-14
Format: Paperback
ISBN-13: 9783031458569
DOI: 10.1007/978-3-031-45857-6
Dimensions: 235cm x155cm
Pages: 170