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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Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2025-01-01
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Series: | PLoS Computational Biology |
Online Access: | https://doi.org/10.1371/journal.pcbi.1012749 |
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