Article

Generalising uncertainty improves accuracy and safety of deep learning analytics applied to oncology

2022-08-29

Abstract excerpt

<title>Abstract</title> <p>Trust and transparency are critical for deploying deep learning (DL) models into the clinic. DL application poses generalisation obstacles since training/development datasets often have different data distributions to clinical/production datasets that can lead to incorrect predictions with underestimated uncertainty. To investigate this pitfall, we benchmarked one pointwise and three ap...

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Literature Corpus work: 0ec772c2-6ea9-543f-8ecc-f8a8ed7bd8be
DOI: 10.21203/rs.3.rs-1984539/v1

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