Classification method for disease risk mapping based on discrete hidden Markov random fields.

@article{CharrasGarrido2012ClassificationMF,
  title={Classification method for disease risk mapping based on discrete hidden Markov random fields.},
  author={M. Charras-Garrido and D. Abrial and Jocelyn De Go{\"e}r and Sergue{\"i} Dachian and Nathalie Peyrard},
  journal={Biostatistics},
  year={2012},
  volume={13 2},
  pages={241-55}
}
Risk mapping in epidemiology enables areas with a low or high risk of disease contamination to be localized and provides a measure of risk differences between these regions. Risk mapping models for pooled data currently used by epidemiologists focus on the estimated risk for each geographical unit. They are based on a Poisson log-linear mixed model with a latent intrinsic continuous hidden Markov random field (HMRF) generally corresponding to a Gaussian autoregressive spatial smoothing. Risk… CONTINUE READING

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