Comparison of spatial prediction models from Machine Learning of cholangiocarcinoma incidence in Thailand.

Journal: BMC public health
Published Date: Jun 7, 2025

Abstract

BACKGROUND: Cholangiocarcinoma (CCA) poses a significant public health challenge in Thailand, with notably high incidence rates. This study aimed to compare the performance of spatial prediction models using Machine Learning techniques to analyze the occurrence of CCA across Thailand.

Authors

  • Oraya Sahat
    Student of Doctor of Public Health Program, Faculty of Public Health, Khon Kaen University, Khon Kaen, Thailand.
  • Supot Kamsa-Ard
    Department of Epidemiology and Biostatistics, Faculty of Public Health, Khon Kaen University, Khon Kaen, Thailand. supot@kku.ac.th.
  • Apiradee Lim
    Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani Campus, Pattani, Thailand.
  • Siriporn Kamsa-Ard
    Department of Epidemiology and Biostatistics, Faculty of Public Health, Khon Kaen University, Khon Kaen, Thailand.
  • Matias Garcia-Constantino
    School of Computing, Ulster University, Jordanstown BT37 0QB, UK.
  • Idongesit Ekerete
    School of Computing, Ulster University, Northern Ireland, Belfast Campus, Belfast, BT15 1 AP, UK.

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