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Aggregating multiple test results to improve medical decision-making.
Gathering observational data for medical decision-making often involves uncertainties arising from both type I (false positive) and type II (false negative) errors. In this work, we develop a statistical model to study how medical decision-making can be improved by aggregating results from repeated...
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| Autori principali: | , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Public Library of Science (PLoS)
2025-01-01
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| Serie: | PLoS Computational Biology |
| Accesso online: | https://doi.org/10.1371/journal.pcbi.1012749 |
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