Prediction of urinary tract infection using machine learning methods: a study for finding the most-informative variables
Abstract Background Urinary tract infection (UTI) is a frequent health-threatening condition. Early reliable diagnosis of UTI helps to prevent misuse or overuse of antibiotics and hence prevent antibiotic resistance. The gold standard for UTI diagnosis is urine culture which is a time-consuming and...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-01-01
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| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12911-024-02819-2 |
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