Matthias I. Gröschel

This paper presents a deep convolutional neural network to predict antibiotic resistance in M. tuberculosis isolates, achieving state-of-the-art accuracy and enabling interpretable feature analysis.

GenTB predicts tuberculosis drug resistance from genomic data using machine learning, achieving higher sensitivity than existing tools with slightly lower specificity.

The paper analyzes global S. maltophilia strains to show genetic diversity and intra-hospital transmission.