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Semi-Supervised Tumor Response Grade Classification from Histology Images of Colorectal Liver Metastases.

, , , , , , , and . ISBI, page 1-5. IEEE, (2022)

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Semi-Supervised Tumor Response Grade Classification from Histology Images of Colorectal Liver Metastases., , , , , , , and . ISBI, page 1-5. IEEE, (2022)Semi-supervised ViT knowledge distillation network with style transfer normalization for colorectal liver metastases survival prediction., , , , , , , , , and . CoRR, (2023)Ensemble Tabnet Predicting a T-Cell/MHC-I-Based Immune Profile Biomarker for Colorectal Liver Metastases from CT Images., , , , and . ISBI, page 1-5. IEEE, (2023)RNA sequencing-based histological subtyping of non-small cell lung cancer with generative adversarial data imputation., , , and . BHI, page 1-4. IEEE, (2023)Verbal or visual cues: impacts of familiarity and attention., , , and . PETRA, page 80. ACM, (2016)End-To-End Discriminative Deep Network For Liver Lesion Classification., , , , , , , and . ISBI, page 1243-1246. IEEE, (2019)Predicting the Response to FOLFOX-Based Chemotherapy Regimen from Untreated Liver Metastases on Baseline CT: a Deep Neural Network Approach., , , , , , , , , and . J. Digit. Imaging, 33 (4): 937-945 (2020)Prediction of CD3 T-cell infiltration status in colorectal liver metastases: a radiomics-based imaging biomarker., , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 12033 of SPIE Proceedings, SPIE, (2022)