refineR: A Novel Algorithm for Reference Interval Estimation from Real-World Data
Abstract Reference intervals are essential for the interpretation of laboratory test results in medicine. We propose a novel indirect approach to estimate reference intervals from real-world data as an alternative to direct methods, which require samples from healthy individuals. The presented refin...
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Auteurs principaux: | , , , , , |
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Format: | article |
Langue: | EN |
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Nature Portfolio
2021
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Accès en ligne: | https://doaj.org/article/e221b54fbd294da994f4057aa0be46c4 |
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