A new deep learning approach predicts tuberculosis drug resistance directly from genetic sequences with diagnostic accuracy, and validates clinical relevance by identifying patients at risk of treatment failure. Original paper: Convolutional neural networks quantify antibiotic resistance in Mycobacterium tuberculosis with diagnostic grade accuracy and predict treatment response. — Nature communications. 10.1038/s41467-026-72225-x 📄 Read the article