Semi-Supervised Variational Autoencoder for Survival Prediction

10 Oct 2019Sveinn PálssonStefano CerriAndrea DittadiKoen Van Leemput

In this paper we propose a semi-supervised variational autoencoder for classification of overall survival groups from tumor segmentation masks. The model can use the output of any tumor segmentation algorithm, removing all assumptions on the scanning platform and the specific type of pulse sequences used, thereby increasing its generalization properties... (read more)

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