Machine learning models diagnose oral squamous cell carcinoma based on cross-cohort oral microbial signatures

Our study provides a robust non-invasive diagnostic model for OSCC and demonstrates that high diagnostic accuracy is achievable at both genus and species levels, suggesting that taxonomic resolution is not the primary limiting factor. Instead, the choice of model construction methods is crucial. Therefore, greater attention should be paid to the selection of model methods in clinical applications.