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Incorporating uncertainty in learning to defer algorithms for safe computer-aided diagnosis
Deep neural networks are increasingly being used for computer-aided diagnosis, but erroneous diagnoses can be extremely costly for patients. We propose a learning to defer with uncertainty (LDU) algorithm which identifies patients for whom diagnostic uncertainty is high and defers them for evaluatio...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8810991/ https://www.ncbi.nlm.nih.gov/pubmed/35110629 http://dx.doi.org/10.1038/s41598-022-05725-7 |