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Radiomics-Dosiomics-Contouromics Collaborative Learning for Adaptive Radiotherapy Eligibility Prediction in Nasopharyngeal Carcinoma.

, , , , , and . BIBM, page 3991-3997. IEEE, (2023)

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Multi-institutional Investigation of Model Generalizability for Virtual Contrast-Enhanced MRI Synthesis., , , , , , , , , and 5 other author(s). MICCAI (8), volume 13437 of Lecture Notes in Computer Science, page 765-773. Springer, (2022)Multi-view Contrastive Learning with Additive Margin for Adaptive Nasopharyngeal Carcinoma Radiotherapy Prediction., , , , , , and . CoRR, (2022)Integration of an imbalance framework with novel high-generalizable classifiers for radiomics-based distant metastases prediction of advanced nasopharyngeal carcinoma., , , , , , , , , and . Knowl. Based Syst., (2022)Multi-view Contrastive Learning with Additive Margin for Adaptive Nasopharyngeal Carcinoma Radiotherapy Prediction., , , , , , and . ICMR, page 555-559. ACM, (2023)Radiomics-Dosiomics-Contouromics Collaborative Learning for Adaptive Radiotherapy Eligibility Prediction in Nasopharyngeal Carcinoma., , , , , and . BIBM, page 3991-3997. IEEE, (2023)Repeatability of Radiomic Features Against Simulated Scanning Position Stochasticity Across Imaging Modalities and Cancer Subtypes: A Retrospective Multi-institutional Study on Head-and-Neck Cases., , , , , , , , , and 3 other author(s). CMMCA@MICCAI, volume 13574 of Lecture Notes in Computer Science, page 21-34. Springer, (2022)