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As if sand were stone. New concepts and metrics to probe the ground on which to build trustable AI
BACKGROUND: We focus on the importance of interpreting the quality of the labeling used as the input of predictive models to understand the reliability of their output in support of human decision-making, especially in critical domains, such as medicine. METHODS: Accordingly, we propose a framework...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7488864/ https://www.ncbi.nlm.nih.gov/pubmed/32917183 http://dx.doi.org/10.1186/s12911-020-01224-9 |