A novel approach for standardizing clinical laboratory categorical test results using machine learning and string distance similarity

Standardizing clinical laboratory test results is critical for conducting clinical data science research and analysis. However, standardized data processing tools and guidelines are inadequate. In this paper, a novel approach for standardizing categorical test results based on supervised machine lea...

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Detalles Bibliográficos
Autores principales: Ahmmed, Syed, Mondal, M. Rubaiyat Hossain, Mia, Md Raihan, Adibuzzaman, Mohammad, Hoque, Abu Sayed Md. Latiful, Ahamed, Sheikh Iqbal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10685145/
https://www.ncbi.nlm.nih.gov/pubmed/38034661
http://dx.doi.org/10.1016/j.heliyon.2023.e21523

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10685145/
https://www.ncbi.nlm.nih.gov/pubmed/38034661
http://dx.doi.org/10.1016/j.heliyon.2023.e21523

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