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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...
Autores principales: | Ahmmed, Syed, Mondal, M. Rubaiyat Hossain, Mia, Md Raihan, Adibuzzaman, Mohammad, Hoque, Abu Sayed Md. Latiful, Ahamed, Sheikh Iqbal |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
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 |
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