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02/15/2022
Improving the repeatability of deep learning models with Monte Carlo dropout
The integration of artificial intelligence into clinical workflows requi...
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11/12/2021
Monte Carlo dropout increases model repeatability
The integration of artificial intelligence into clinical workflows requi...
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09/09/2021
Fair Conformal Predictors for Applications in Medical Imaging
Deep learning has the potential to augment many components of the clinic...
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07/06/2021
Evaluating subgroup disparity using epistemic uncertainty in mammography
As machine learning (ML) continue to be integrated into healthcare syste...
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08/06/2020
Assessing the (Un)Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging
Saliency maps have become a widely used method to make deep learning mod...
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11/14/2019
Give me (un)certainty – An exploration of parameters that affect segmentation uncertainty
Segmentation tasks in medical imaging are inherently ambiguous: the boun...
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08/14/2018
