A team led by researchers from the ETH Zürich and the University of Basel has used a combination of mass spectrometry data and machine learning to predict antibiotic resistance of clinical bacterial samples. The results, which were published in the Jan. 10, 2022, issue of Nature Medicine, could speed the identification of optimal antibiotic regimens for patients.