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Gene to Morphology Alignment via Graph Constrained Latent Modeling for Molecular Subtype Prediction from Histopathology in Pancreatic Cancer
2026-03-06
oncology
Title + abstract only
View on medRxiv
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Molecular subtyping of cancer is traditionally defined in transcriptomic space, yet routine clinical deployment is limited by the availability and cost of sequencing. Meanwhile, histopathology captures rich morphological information that is known to correlate with molecular state but lacks a principled, mechanistic bridge to gene-level representations. We propose a graph-constrained learning framework that aligns morphology-derived signals with a fixed, data-driven gene network discovered via hi...
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