Translational impact of machine learning-driven predictive modeling with pathway-based plasma metabolomic biomarkers for lung cancer detection

This noninvasive, interpretable approach using plasma panel could facilitate cost-effective, early-stage lung cancer screening for at high-risk population cohort, with strong translational potential in clinical settings. Future work should focus on multi-center validation, prospective validation, assessing potential longitudinal biomarker stability, and integration with other omics data to further advance precision oncology, ultimately improving early detection and patient outcomes in lung cancer management.