A data-driven universal gut microbiome health assessment: a machine learning framework trained on large metagenomic data
Results show that models trained on pooled metagenomes predict gut health status accurately and transfer to independent cohorts, providing a scalable, non-invasive framework and a set of candidate microbial biomarkers for further clinical evaluation.