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pro vyhledávání: '"Morsomme, Raphaël"'
Multi-state models of cancer natural history are widely used for designing and evaluating cancer early detection strategies. Calibrating such models against longitudinal data from screened cohorts is challenging, especially when fitting non-Markovian
Externí odkaz:
http://arxiv.org/abs/2408.14625
Throughout the course of an epidemic, the rate at which disease spreads varies with behavioral changes, the emergence of new disease variants, and the introduction of mitigation policies. Estimating such changes in transmission rates can help us bett
Externí odkaz:
http://arxiv.org/abs/2211.14691
Autor:
Morsomme, Raphael, Xu, Jason
Stochastic epidemic models provide an interpretable probabilistic description of the spread of a disease through a population. Yet, fitting these models to partially observed data is a notoriously difficult task due to intractability of the likelihoo
Externí odkaz:
http://arxiv.org/abs/2201.09722
Akademický článek
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Autor:
Morsomme, Raphaël, Smirnov, Evgueni
Publikováno v:
Proceedings of Machine Learning Research: Conformal and Probabilistic Prediction and Applications, 9-11 September 2019, Golden Sands, Bulgaria, 105, 196-213
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=narcis______::a0d3e8ec4f66ab23d60d2aae8b474ca2
https://cris.maastrichtuniversity.nl/en/publications/5cc0931f-2a7a-4597-95f2-1caa331b9a63
https://cris.maastrichtuniversity.nl/en/publications/5cc0931f-2a7a-4597-95f2-1caa331b9a63