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Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection
Despite impressive state-of-the-art performance on a wide variety of machine learning tasks in multiple applications, deep learning methods can produce over-confident predictions, particularly with limited training data. Therefore, quantifying uncertainty is particularly important in critical applic...
Autores principales: | Akrami, Haleh, Joshi, Anand A., Aydöre, Sergül, Leahy, Richard M. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9881592/ https://www.ncbi.nlm.nih.gov/pubmed/36712144 |
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