Interpretable machine learning-based decision support for prediction of antibiotic resistance for complicated urinary tract infections
Urinary tract infections are one of the most common bacterial infections worldwide; however, increasing antimicrobial resistance in bacterial pathogens is making it challenging for clinicians to correctly prescribe patients appropriate antibiotics. In this study, we present four interpretable machin...
| Κύριοι συγγραφείς: | , , , |
|---|---|
| Μορφή: | Journal article |
| Γλώσσα: | English |
| Έκδοση: |
Springer Nature
2023
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