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This study developed a unique rapid pathological diagnosis and staging technique for intraoperative tissue sections based on lipidomic relevance, using two-photon fluorescence (TPF) imaging assisted by a lipid-targeted carbonized polymer dot (CPD) probe (\u223c8 nm) and multiple classification algorithms, including machine learning and deep convolutional networks. This platform enables ultrabright TPF imaging in response to lipid microenvironments and can be completed within 10 min. Its feasibility was validated through rapid diagnostics of intraoperative frozen sections of breast tissues. Due to abnormal levels of lipid metabolism, normal breast tissues and pathologically staged I\u2013III cancerous tissues were well distinguishable, and the sensitivities and specificities for pathologic diagnosis were all above 90%. The combination of CPD and TPF microscopy provides a rapid and accurate method for detecting lipidomes in pathological frozen sections, marking a significant advancement over hematoxylin and eosin (H&amp;E)-staining-based pathological diagnosis in terms of speed, ease of operation, and relevance to chemical components. 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