A machine learning framework for classifying lipids in untargeted metabolomics using mass-to-charge ratios and retention times

Our results demonstrate that metabolites can be classified as "lipid", "non-lipid" using only m/z and RT from untargeted LC-MS data, without requiring MS2 spectra. Although this study focused on lipid classification, the approach shows potential for broader application, which warrants further investigation across diverse compound classes, detection methods, and chromatographic conditions.