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Evaluating growth and risk of relapse of intracranial tumors

Abstract : As cancer evolution is challenging to evaluate, there is dire need of novel approaches offering clinicians a better insight on the disease. For instance, having an estimation of the growth of slowly evolving tumors that have to be monitored or of the risk of relapse after treatment may be invaluable for clinicians. In this article, two approaches (statistical learning and mechanistic modelling) are presented that aim at addressing these clinical questions. As we wish to use data available in the clinical routine for solid tumors, medical images will be a major source of insight on the disease.
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Submitted on : Thursday, December 12, 2019 - 11:17:26 AM
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  • HAL Id : hal-02406709, version 1



Olivier Saut, Thierry Colin, Annabelle Collin, Thibaut Kritter, Vivien Pianet, et al.. Evaluating growth and risk of relapse of intracranial tumors. Computational Systems Biology Approaches in Cancer Research, CRC Press, 2019, 9780367344214. ⟨hal-02406709⟩



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