Uncertainty for Safe Utilization of Machine Learning in Medical Imaging
William M. Wells III, Koen Van Leemput, Ryutaro Tanno, Chen Qin, Adrian Dalca, Christian F. Baumgartner, Carole H. Sudre
815 kr
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For UNSURE 2020, 10 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world.
GRAIL 2020 accepted 10 papers from the 12 submissions received. The workshop aims to bring together scientists that use and develop graph-based models for the analysis of biomedical images and to encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts.