Lab2clean: a novel algorithm for automated cleaning of retrospective clinical laboratory results data for secondary uses.

ABSTRACT:

Background

The integrity of clinical research and machine learning models in healthcare heavily relies on the quality of underlying clinical laboratory data. However, the preprocessing of this data to ensure its reliability and accuracy remains a significant challenge due to variations in data recording and reporting standards.

Methods

We developed lab2clean, a novel algorithm aimed at automating and standardizing the cleaning of retrospective clinical laboratory results data. lab2clean was implemented as two R functions specifically designed to enhance data conformance and plausibility by standardizing result formats and validating result values. The functionality and performance of the algorithm were evaluated using two extensive electronic medical record (EMR) databases,

SUBMITTER: Zayed AM 

PROVIDER: S-EPMC11370074 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature