Predicting laboratory solution kit accuracy using artificial intelligence: a data-driven approach

Predicting laboratory solution kit accuracy using artificial intelligence: a data-driven approach

Abstract This study developed and validated an artificial intelligence (AI)-based computational tool for standardizing glucose and urea measurements across different clinical laboratory systems (Biolabo and BioScien) using Biomagreb as the reference standard. Through empirical analysis of parallel-t...

Full description

Saved in:
Bibliographic Details
Main Authors: Abdulwahab AL-Deib, Eshraq Alsherif, Husameddin Abuzgaia, Amel Rabti, Ruwaida Rtemi, Salem Elfard, Sheren Njaim
Format: Article
Language:English
Published: SpringerOpen 2025-08-01
Series:Bulletin of the National Research Centre
Subjects:
Artificial intelligence
Linear regression
Diagnostic accuracy
Medical laboratory department
University of Tripoli Alahlia
Online Access:https://doi.org/10.1186/s42269-025-01351-1
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1186/s42269-025-01351-1

Similar Items