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Out-of-Distribution Detection for Medical Applications: Guidelines for Practical Evaluation. (arXiv:2109.14885v2 [cs.LG] UPDATED)
May 9, 2022, 1:11 a.m. | Karina Zadorozhny, Patrick Thoral, Paul Elbers, Giovanni Cinà
cs.LG updates on arXiv.org arxiv.org
Detection of Out-of-Distribution (OOD) samples in real time is a crucial
safety check for deployment of machine learning models in the medical field.
Despite a growing number of uncertainty quantification techniques, there is a
lack of evaluation guidelines on how to select OOD detection methods in
practice. This gap impedes implementation of OOD detection methods for
real-world applications. Here, we propose a series of practical considerations
and tests to choose the best OOD detector for a specific medical dataset. These …
applications arxiv detection distribution evaluation guidelines medical
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