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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| Published in: | Heliyon Vol. 9; no. 11; p. e21523 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
England
Elsevier Ltd
01.11.2023
Elsevier |
| Subjects: | |
| ISSN: | 2405-8440, 2405-8440 |
| Online Access: | Get full text |
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