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

Journal of Medical Systems
Alberto CalzadaLuis Martinez

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 syste...Continue Reading

References

Jun 19, 2007·Journal of Clinical Epidemiology·Cornelia H M van JaarsveldJane Wardle
Jun 26, 2009·Social Science & Medicine·Malavika SubramanyamS V Subramanian

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Citations

Feb 1, 2017·Journal of Medical Systems·Mohammad Shahadat HossainKarl Andersson

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