A Multianalyte Machine Learning Model to Detect Wrong Blood in Complete Blood Count Tube Errors in a Pediatric Setting.
Background Multianalyte machine learning (ML) models can potentially identify previously undetectable wrong blood in tube (WBIT) errors, improving upon current single-analyte delta check methodology. However, WBIT detection model performance has not been assessed in a real-world, low-prevalence cont...
| Publicado en: | Clinical Chemistry Vol. 71; no. 3; pp. 418 - 428 |
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| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
Oxford University Press / USA
Mar2025
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| Acceso en línea: | Ver este registro en EBSCOhost |