Machine learning and phylogenetic analysis allow for predicting antibiotic resistance in M. tuberculosis
Abstract Background Antimicrobial resistance (AMR) poses a significant global health threat, and an accurate prediction of bacterial resistance patterns is critical for effective treatment and control strategies. In recent years, machine learning (ML) approaches have emerged as powerful tools for an...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-12-01
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| Series: | BMC Microbiology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12866-023-03147-7 |