Application of a Spatial Intelligent Decision System on Self-Rated Health Status Estimation.
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...
| Publicado en: | Journal of Medical Systems Vol. 39; no. 11; pp. 1 - 19 |
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| Autores principales: | , , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Nov2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=115925211&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 115925211 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Nov2015 vid: 39 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 115925211 115925211 115925211 10.1007/s10916-015-0321-4 115925211 ppf: 1 ppct: 18 formats: fmt: @attributes: type: P tig: atl: Application of a Spatial Intelligent Decision System on Self-Rated Health Status Estimation. aug: au: Calzada, Alberto Liu, Jun Wang, Hui Nugent, Chris Martinez, Luis affil: School of Computing and Mathematics, Ulster University, Northern Ireland UK sug: subj: Health Status Northern Ireland Self Assessment Decision Making Geographic Locations Decision Support Techniques Geographic Information Systems Northern Ireland Social Determinants of Health Maps Human ab: 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. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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