@inbook{ef1ca13afd1e4ae9bcb3ebcf7786f4c6,
title = "Using the spatial RIMER+ approach to estimate negative self-rated health and its causes across Northern Ireland",
abstract = "Self-rated health is a commonly-used survey technique that helps collecting information about the public health in an area. It is widely recognized that self-rated health has a strong correlation with key public-health variables such as deprivation, poverty, fear of crime or mortality. Therefore, it is a useful tool when assessing the public health situation of a neighborhood or town. This paper utilizes a recently-developed decision framework, named, Spatial RIMER+, to model a decision problem using real data where self-rated health is unknown in certain areas of Northern Ireland and needs to be estimated. The results retrieved in the study demonstrate the high accuracy of the methodology as well as its the flexibility and applicability to model a wide range of spatial decision scenarios.",
keywords = "Knowledge representation, Self-Rated Health, Spatial Decision Support Rule-Based Systems Knowledge-based approach",
author = "Alberto Calzada and Jun Liu and Chris Nugent and Hui Wang and Luis Martinez",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2014.",
year = "2014",
doi = "10.1007/978-3-319-13102-3_52",
language = "English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "312--319",
editor = "Ram{\'o}n Herv{\'a}s and Jos{\'e} Bravo and Sungyoung Lee and Chris Nugent",
booktitle = "Ubiquitous Computing and Ambient Intelligence",
}
