lab2clean: a novel algorithm for automated cleaning of retrospective clinical laboratory results data for secondary uses

lab2clean addresses the challenge of preprocessing and cleaning clinical laboratory data, a critical step in ensuring high-quality data for research outcomes. It offers a straightforward, efficient tool for researchers, improving the quality of clinical laboratory data, a major portion of healthcare data. Thereby, enhancing the reliability and reproducibility of clinical research outcomes and clinical machine learning models. Future developments aim to broaden its functionality and accessibility, solidifying its vital role in healthcare data management.

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Publication Details

Journal
BMC Medical Informatics and Decision Making
Published
2024-09-03
DOI
https://doi.org/10.1186/s12911-024-02652-7
Citations
3
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
1.39
Controls
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article

lab2clean: a novel algorithm for automated cleaning of retrospective clinical laboratory results data for secondary uses

Pavlos Mamouris, Nicolas Delvaux, Ahmed Medhat Zayed, Arne Janssens
3 citations
BMC Medical Informatics and Decision Making
Machine Learning in Healthcare
1.39
article

lab2clean: a novel algorithm for automated cleaning of retrospective clinical laboratory results data for secondary uses

Pavlos Mamouris, Nicolas Delvaux, Ahmed Medhat Zayed, Arne Janssens
article en
3 citations

Abstract

lab2clean addresses the challenge of preprocessing and cleaning clinical laboratory data, a critical step in ensuring high-quality data for research outcomes. It offers a straightforward, efficient tool for researchers, improving the quality of clinical laboratory data, a major portion of healthcare data. Thereby, enhancing the reliability and reproducibility of clinical research outcomes and clinical machine learning models. Future developments aim to broaden its functionality and accessibility, solidifying its vital role in healthcare data management.

BMC Medical Informatics and Decision MakingVol. 24(1)
Department of Public Health (US), Menoufia University (EG), KU Leuven (BE)
Industry, innovation and infrastructure
Openalex Percentile: Top 16%
Machine Learning in Healthcare
1.39
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