lab2clean: 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)' <doi:10.1186/s12911-024-02652-7>. Functions to standardize & harmonize result units (added in Version 2.0) are described in detail in 'Zayed et al. (2025)' <doi:10.1016/j.ijmedinf.2025.106131>.
Version: |
2.0.0 |
Depends: |
R (≥ 3.5) |
Imports: |
data.table, stats, utils |
Suggests: |
knitr, rmarkdown, fansi, kableExtra, printr |
Published: |
2025-10-04 |
DOI: |
10.32614/CRAN.package.lab2clean |
Author: |
Ahmed Zayed [aut,
cre],
Ilias Sarikakis [aut, ctb],
Arne Janssens [aut, ctb],
Pavlos Mamouris [ctb] |
Maintainer: |
Ahmed Zayed <ahmed.zayed at kuleuven.be> |
License: |
GPL (≥ 3) |
NeedsCompilation: |
no |
CRAN checks: |
lab2clean results |
Documentation:
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