Web: http://arxiv.org/abs/2109.04392

May 4, 2022, 1:12 a.m. | Charles Lu, Andreanne Lemay, Ken Chang, Katharina Hoebel, Jayashree Kalpathy-Cramer

cs.LG updates on arXiv.org arxiv.org

Deep learning has the potential to automate many clinically useful tasks in
medical imaging. However translation of deep learning into clinical practice
has been hindered by issues such as lack of the transparency and
interpretability in these "black box" algorithms compared to traditional
statistical methods. Specifically, many clinical deep learning models lack
rigorous and robust techniques for conveying certainty (or lack thereof) in
their predictions -- ultimately limiting their appeal for extensive use in
medical decision-making. Furthermore, numerous demonstrations of …

applications arxiv imaging medical medical imaging

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