Uncertainty quantification on a spatial Markov-chain model for the progression of skin cancer

Fred Vermolen, Ilkka Pölönen

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
14 Downloads (Pure)

Abstract

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.

Original languageEnglish
Pages (from-to)1-29
Number of pages29
JournalJournal of Mathematical Biology
DOIs
Publication statusE-pub ahead of print - 2019

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