Method development improves laboratory data quality in oncology, suggesting a new scalable solution.
Laboratory data quality is crucial in oncology systems for therapy selection, monitoring, and disease progression assessment. This proposed solution is a first-of-its-kind, system-agnostic, and scalable normalization process that addresses key gaps in laboratory data quality across multiple dimensions.
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Naliyatthaliyazchayil et al. (2026) studied this question.
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