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3D Deep Attention Network for Survival Prediction from Magnetic Resonance Images in Glioblastoma.

, , , , , and . ICIP, page 1381-1384. IEEE, (2019)

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Solving Static Optimal Matching Problem in Heterogeneous Processing with Generalized Stable Marriage Algorithms.. IPPS, page 248-252. IEEE Computer Society, (1994)Pathology-genomic fusion via biologically informed cross-modality graph learning for survival analysis., , , , , , , and . CoRR, (2024)Towards an Interpretable Radiomics Model for Classifying Renal Cell Carcinomas Subtypes: A Radiogenomics Assessment., , , , , and . ISBI, page 1288-1292. IEEE, (2019)3D Deep Attention Network for Survival Prediction from Magnetic Resonance Images in Glioblastoma., , , , , and . ICIP, page 1381-1384. IEEE, (2019)DeepPhase: Learning phase contrast signal from dual energy X-ray absorption images., , , , and . Displays, (2021)Automatic Extraction of MRI Radiomics Features in Glioblastoma Multiforme: A Reproducibility Evaluation., , , , and . CYBCONF, page 1-4. IEEE, (2017)MRI and RNA-seq fusion for prediction of pathological response to neoadjuvant chemotherapy in breast cancer., , , , , , , and . Displays, (2024)Dual-region radiomics signature: Integrating primary tumor and lymph node computed tomography features improves survival prediction in esophageal squamous cell cancer., , , , , , , , , and . Comput. Methods Programs Biomed., (2021)