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Predicting Esophageal Fistula Risks Using a Multimodal Self-attention Network.

, , , , , , , , , and . MICCAI (5), volume 12905 of Lecture Notes in Computer Science, page 721-730. Springer, (2021)

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Shape-aware contrastive deep supervision for esophageal tumor segmentation from CT scans., , , , , , , , , and . BIBM, page 1188-1193. IEEE, (2023)Predicting Esophageal Fistula Risks Using a Multimodal Self-attention Network., , , , , , , , , and . MICCAI (5), volume 12905 of Lecture Notes in Computer Science, page 721-730. Springer, (2021)Co-graph Attention Reasoning Based Imaging and Clinical Features Integration for Lymph Node Metastasis Prediction., , , , , , , , , and 2 other author(s). MICCAI (5), volume 12905 of Lecture Notes in Computer Science, page 657-666. Springer, (2021)Collaborative Learning of Cross-channel Clinical Attention for Radiotherapy-Related Esophageal Fistula Prediction from CT., , , , and . MICCAI (1), volume 12261 of Lecture Notes in Computer Science, page 212-220. Springer, (2020)