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Machine learning models outperform manual result review for the identification of wrong blood in tube errors in complete blood count results
12
Zitationen
2
Autoren
2022
Jahr
Abstract
This study provides preliminary evidence supporting the value of machine learning for detecting WBIT errors affecting CBC results. Although further work addressing practical issues is required, substantial patient-safety benefits await the successful deployment of machine learning models for WBIT error detection.
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