6533b7cefe1ef96bd1257125
RESEARCH PRODUCT
Uncertainty quantification on a spatial Markov-chain model for the progression of skin cancer
Fred J. VermolenIlkka Pölönensubject
65C05Skin NeoplasmsComputer scienceQuantitative Biology::Tissues and OrgansMarkovin ketjut0206 medical engineeringMonte Carlo methodPhysics::Medical PhysicsBinary number02 engineering and technologyArticleihosyöpä03 medical and health sciencesMicemedicineAnimalsHumansComputer SimulationStatistical physicsUncertainty quantification60J20stokastiset prosessit030304 developmental biologyProbability0303 health sciencesMarkov chainApplied MathematicsProbabilistic logicUncertaintyState (functional analysis)medicine.disease020601 biomedical engineeringAgricultural and Biological Sciences (miscellaneous)Markov ChainsCardinal pointModeling and Simulation65C40Disease Progressionmatemaattiset mallitSkin cancerMonte Carlo Methoddescription
AbstractA 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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-12-01 | Journal of Mathematical Biology |