Machine learning prediction of human antibiotic resistance risk using 16S rRNA profiles.
This work establishes a scalable framework for inferring antibiotic resistance risk from 16S data, enabling equitable, large-scale surveillance of antimicrobial resistance while positioning microbiome composition as a predictive basis for functional risk and advancing a general paradigm for inferring microbial traits f...