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  The future of spatial epidemiology in the AI era: enhancing machine learning approaches with explicit spatial structure

  Nima Kianfar, Benn Sartorius, Colleen L. Lau, Robert Bergquist, Behzad Kiani

  04-06-2025

  https://doi.org/10.4081/gh.2025.1386

  2539

  PDF: 496

  HTML: 34
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  Identifying counties vulnerable to diabetes from obesity prevalence in the United States: a spatiotemporal analysis

  Xiao Li, Amanda Staudt, Lung-Chang Chien

  21-11-2016

  https://doi.org/10.4081/gh.2016.439

  2738

  PDF: 1297

  APPENDIX: 469

  HTML: 1139

• Spatial associations between chronic kidney disease and socio-economic factors in Thailand

  Juree Sansuk, Kittipong Sornlorm

  30-01-2024

  https://doi.org/10.4081/gh.2024.1246

  6366

  PDF: 1036

  HTML: 1106
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  Space-time clustering characteristics of dengue based on ecological, socio-economic and demographic factors in northern Sri Lanka

  Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran

  26-11-2015

  https://doi.org/10.4081/gh.2015.376

  3768

  PDF: 2183

  HTML: 1268