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Application of a Spatial Intelligent Decision System on Self-Rated Health Status Estimation

  • Systems-Level Quality Improvement
  • Published:
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Abstract

Self- assessed general health status is a commonly-used survey technique since it can be used as a predictor for several public health risks such as mortality, deprivation, and fear of crime or poverty. Therefore, it is a useful alternative measure to help assessing the public health situation of a neighborhood or town, and can be utilized by authorities in many decision support situations related to public health, budget allocation and general policy-making, among others. It can be considered as spatial decision problems, since both data location and spatial relationships make a prominent impact during the decision making process. This paper utilizes a recently-developed spatial intelligent decision system, named, Spatial RIMER+, to model the self-rated health estimation decision problem using real data in the areas of Northern Ireland, UK. The goal is to learn from past or partial observations on self-rated health status to predict its future or neighborhood behavior and reference it in the map. Three scenarios in line of this goal are discussed in details, i.e., estimation of unknown, downscaling, and predictions over time. They are used to demonstrate the flexibility and applicability of the spatial decision support system and their positive capabilities in terms of accuracy, efficiency and visualization.

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Authors and Affiliations

  1. School of Computing and Mathematics, Ulster University, Northern Ireland, UK

    Alberto Calzada, Jun Liu, Hui Wang & Chris Nugent

  2. Department of Computer Science, University of Jaen, Jaen, Spain

    Luis Martinez

Authors
  1. Alberto Calzada
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  2. Jun Liu
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  3. Hui Wang
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  4. Chris Nugent
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  5. Luis Martinez
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Corresponding author

Correspondence to Jun Liu.

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This article is part of the Topical Collection on Systems-Level Quality Improvement

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Calzada, A., Liu, J., Wang, H. et al. Application of a Spatial Intelligent Decision System on Self-Rated Health Status Estimation. J Med Syst 39, 138 (2015). https://doi.org/10.1007/s10916-015-0321-4

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  • DOI: https://doi.org/10.1007/s10916-015-0321-4

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