Results 151 to 160 of about 527,565 (212)
Disease mapping of zero-excessive mesothelioma data in Flanders. [PDF]
Ann Epidemiol, 2017 Neyens T +8 more
europepmc +1 more source
Evaluation of threshold selection methods for adaptive kernel density estimation in disease mapping. [PDF]
Int J Health Geogr, 2018 Ruckthongsook W +3 more
europepmc +1 more source
Smartphone-Based Mobile Detection Platform for Molecular Diagnostics and Spatiotemporal Disease Mapping. [PDF]
Anal Chem, 2018 Song J +6 more
europepmc +1 more source
Bayesian disease mapping: Past, present, and future [PDF]
Spatial Statistics, 2022 Ying C Macnab
exaly +2 more sources
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Ophthalmic Paediatrics and Genetics, 1992
In this review the authors first give an overview of the general strategies of mapping which differ whether the biochemical (molecular) defect of the disease is known or not. The main problems besides mapping are concerned for the first category with the correlation between mutation and phenotype and for the second, with heterogeneity, genetic vs ...
J, Frézal, J, Kaplan, H, Dollfus
openaire +2 more sources
In this review the authors first give an overview of the general strategies of mapping which differ whether the biochemical (molecular) defect of the disease is known or not. The main problems besides mapping are concerned for the first category with the correlation between mutation and phenotype and for the second, with heterogeneity, genetic vs ...
J, Frézal, J, Kaplan, H, Dollfus
openaire +2 more sources
Estimation in Bayesian Disease Mapping
Biometrics, 2004SummaryRecent work on Bayesian inference of disease mapping models discusses the advantages of the fully Bayesian (FB) approach over its empirical Bayes (EB) counterpart, suggesting that FB posterior standard deviations of small‐area relative risks are more reflective of the uncertainty associated with the relative risk estimation than counterparts ...
MacNab, Ying C. +3 more
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Statistics in Medicine, 2001
AbstractThe analysis of the geographical distribution of disease incidence or prevalence is now of considerable importance for public health workers and epidemiologists alike. Important disease variations often have a spatial expression and so spatial analysis methods are an important additional tool in this connection. In this tutorial I have aimed to
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AbstractThe analysis of the geographical distribution of disease incidence or prevalence is now of considerable importance for public health workers and epidemiologists alike. Important disease variations often have a spatial expression and so spatial analysis methods are an important additional tool in this connection. In this tutorial I have aimed to
openaire +2 more sources
2019
Disease Mapping: From Foundations to Multidimensional Modeling guides the reader from the basics of disease mapping to the most advanced topics in this field. A multidimensional framework is offered that makes possible the joint modeling of several risks patterns corresponding to combinations of several factors, including age group, time period ...
Miguel A. Martinez-Beneito +1 more
openaire +1 more source
Disease Mapping: From Foundations to Multidimensional Modeling guides the reader from the basics of disease mapping to the most advanced topics in this field. A multidimensional framework is offered that makes possible the joint modeling of several risks patterns corresponding to combinations of several factors, including age group, time period ...
Miguel A. Martinez-Beneito +1 more
openaire +1 more source
DISEASE MAPPING WITH ERRORS IN COVARIATES
Statistics in Medicine, 1997We describe Bayesian hierarchical-spatial models for disease mapping with imprecisely observed ecological covariates. We posit smoothing priors for both the disease submodel and the covariate submodel. We apply the models to an analysis of insulin Dependent Diabetes Mellitus incidence in Sardinia, with malaria prevalence as a covariate.
BERNARDINELLI, LUISA +3 more
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