CenSurv improves cancer survival prediction by modeling patient-modality graphs and converting selected censored samples into uncensored training data via a confidence-based update.
In: Proceedings of the IEEE/CVF Inter- national Conference on Computer Vision
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Bipartite Patient-Modality Graph Learning with Event-Conditional Modelling of Censoring for Cancer Survival Prediction
CenSurv improves cancer survival prediction by modeling patient-modality graphs and converting selected censored samples into uncensored training data via a confidence-based update.