Amr Pipelines

New preprint: A systematic analysis of machine learning pipelines for robust antimicrobial resistance prediction. Across nine clinically relevant species–antibiotic combinations, choices such as k-mer length can shift F1 scores by over 20 points, while tree-based models remain robust and interpretable. With Alex Aselstyne, Enamundram Naga Karthik, Meriem El Azami, Romain Pogorelcnik, and Sarath Chandar. In collaboration with bioMérieux.