Machine Learning for Detecting Iron Deficiency through Comprehensive Blood Analysis.
Journal:
Clinical chemistry
Published Date:
Jul 18, 2025
Abstract
BACKGROUND: Iron deficiency (ID) is a prevalent global health issue with a major impact on well-being. Early detection of ID is crucial but challenging due to its nonspecific symptoms and the limitations of traditional diagnostic tests, which are impractical for large-scale screening. This study proposes a machine learning (ML) approach using complete blood count (CBC) data and cell population data (CPD) for detecting ID in the general population.
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