A hybrid multi-instance learning-based identification of gastric adenocarcinoma differentiation on whole-slide images
Abstract Objective To investigate the potential of a hybrid multi-instance learning model (TGMIL) combining Transformer and graph attention networks for classifying gastric adenocarcinoma differentiation on whole-slide images (WSIs) without manual annotation. Methods and materials A hybrid multi-ins...
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| Hauptverfasser: | , , , , , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
BMC
2025-06-01
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| Schriftenreihe: | BioMedical Engineering OnLine |
| Schlagworte: | |
| Online-Zugang: | https://doi.org/10.1186/s12938-025-01407-3 |
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