Cargando…
DOMINO: Domain-aware loss for deep learning calibration
Deep learning has achieved the state-of-the-art performance across medical imaging tasks; however, model calibration is often not considered. Uncalibrated models are potentially dangerous in high-risk applications since the user does not know when they will fail. Therefore, this paper proposes a nov...
| Autores principales: | , , , , , , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2023
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10118072/ https://www.ncbi.nlm.nih.gov/pubmed/37091721 http://dx.doi.org/10.1016/j.simpa.2023.100478 |