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Showing 1–4 of 4 results
Advanced filters: Author: Philipp G. Keyl Clear advanced filters

  • Risk stratification in non-small cell lung cancer (NSCLC) remains challenging. By combining multiplex immunofluorescence, H&E histology, and AI, the study identifies spatial “cell-niche” patterns that enhance survival prediction beyond UICC8 staging. These patterns reclassify many stage I patients as high risk, revealing potentially undertreated cases and establishing spatial tumor microenvironment features as clinically actionable biomarkers.

    • Simon Schallenberg
    • Gabriel Dernbach
    • Frederick Klauschen
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-25

  • Sinonasal tumour diagnosis can be complicated by the heterogeneity of disease and classification systems. Here, the authors use machine learning to classify sinonasal undifferentiated carcinomas into 4 molecular classe with differences in differentiation state and clinical outcome.

    • Philipp Jurmeister
    • Stefanie Glöß
    • David Capper
    ResearchOpen Access
    Nature Communications
    Volume: 13, P: 1-14