Uncertainty quantification on a spatial Markov-chain model for the progression of skin cancer
Vermolen, F., & Pölönen, I. (2020). Uncertainty quantification on a spatial Markov-chain model for the progression of skin cancer. Journal of Mathematical Biology, 80(3), 545-573. https://doi.org/10.1007/s00285-019-01367-y
Julkaistu sarjassa
Journal of Mathematical BiologyPäivämäärä
2020Tekijänoikeudet
© The Authors 2019
A spatial Markov-chain model is formulated for the progression of skin cancer. The model is based on the division of the computational domain into nodal points, that can be in a binary state: either in ‘cancer state’ or in ‘non-cancer state’. The model assigns probabilities for the non-reversible transition from ‘non-cancer’ state to the ‘cancer state’ that depend on the states of the neighbouring nodes. The likelihood of transition further depends on the life burden intensity of the UV-rays that the skin is exposed to. The probabilistic nature of the process and the uncertainty in the input data is assessed by the use of Monte Carlo simulations. A good fit between experiments on mice and our model has been obtained.
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SpringerISSN Hae Julkaisufoorumista
0303-6812Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/34023017
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