Automation and Standardization of Cleaning Clinical Laboratory Data

Navigating the shift of clinical laboratory data from primary everyday clinical use to secondary research purposes presents a significant challenge. Given the substantial time and expertise required for lab data pre-processing and cleaning and the lack of all-in-one tools tailored for this need, we developed our algorithm 'lab2clean' as an open-source R-package. 'lab2clean' package is set to automate and standardize the intricate process of cleaning clinical laboratory results. With a keen focus on improving the data quality of laboratory result values and units, our goal is to equip researchers with a straightforward, plug-and-play tool, making it smoother for them to unlock the true potential of clinical laboratory data in clinical research and clinical machine learning (ML) model development. Functions to clean & validate result values (Version 1.0) are described in detail in 'Zayed et al. (2024)' . Functions to standardize & harmonize result units (added in Version 2.0) are described in detail in 'Zayed et al. (2025)' .


Reference manual

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install.packages("lab2clean")

2.0.0 by Ahmed Zayed, a year ago


Browse source code at https://github.com/cran/lab2clean


Authors: Ahmed Zayed [aut, cre] , Ilias Sarikakis [aut, ctb] , Arne Janssens [aut, ctb] , Pavlos Mamouris [ctb]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports data.table, stats, utils

Suggests knitr, rmarkdown, fansi, kableExtra, printr


See at CRAN