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Reports and Proceedings
Updates every hour. Last Updated: 8-Apr-2026 02:15 ET (8-Apr-2026 06:15 GMT/UTC)
Machine learning methods have emerged as promising tools to predict antimicrobial resistance (AMR) and uncover resistance determinants from genomic data. This study shows that sampling biases driven by population structure severely undermine the accuracy of AMR prediction models even with large datasets, providing recommendations for evaluating the accuracy of future methods.