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Opening the black box of machine learning in radiology: can the proximity of annotated cases be a way?
Machine learning (ML) and deep learning (DL) systems, currently employed in medical image analysis, are data-driven models often considered as black boxes. However, improved transparency is needed to translate automated decision-making to clinical practice. To this aim, we propose a strategy to open...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7200961/ https://www.ncbi.nlm.nih.gov/pubmed/32372200 http://dx.doi.org/10.1186/s41747-020-00159-0 |