As if sand were stone. New concepts and metrics to probe the ground on which to build trustable AI
Abstract 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 fra...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2020-09-01
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| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12911-020-01224-9 |