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This retrospective study aims to investigate the prognostic significance of artificial intelligence (AI)-powered analysis of tumor-infiltrating lymphocytes (TILs) and the tumor microenvironment (TME) in patients with resected gallbladder cancer. Using hematoxylin and eosin (H&E)-stained slides, the study quantifies spatial TME features, including TIL density, tertiary lymphoid structures, and fibroblast density, to identify potential TME-related risk factors associated with survival.
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