NDLI: Artificial neural networks in analysing health inequalities

Content Provider	IEEE Xplore Digital Library
Author	Zheng Rong Yang
Copyright Year	2002
Description	Author affiliation: Dept. of Comput. Sci., Exeter Univ., UK (Zheng Rong Yang)
Abstract	This paper presents a method of applying artificial neural networks to health structure analysis for Devon, Southwest England. The network used in this study is called unsupervised probabilistic net, with which we can cluster the ward areas within Devon and then quantify the health inequalities in Devon. This paper also presents a new method to analyse the sensitivity of the indicators, by which, the role of each indicator in the formulation of a health inequality structure of Devon can be determined. The data set is provided by Devon health authority containing 252 ward areas within Devon and each ward area is composed of 12 indicators. Through this analysis, it has been found that 75% of the ward areas have similar and better health status whilst the remaining 25% of the ward areas need to be paid attention for reducing the health inequalities within Devon. The sensitivity analysis also shows that 'child poverty', 'employment', 'Breadline' and 'Townsend' play important roles in the health inequality structure of Devon.
Sponsorship	Asia-Pacific Neural Network Assembly Singapore Neuroscience Assoc. SEAL & FSKD Conference Steering Committees IEEE Neural Networks Soc. Int. Neural Network Soc. Eur. Neural Network Soc. SPIE
Starting Page	1966
Ending Page	1971
File Size	440857
Page Count	6
File Format	PDF
ISBN	9810475241
DOI	10.1109/ICONIP.2002.1199017
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-11-18
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Nanyang Technological University
Subject Keyword	Artificial neural networks Intelligent networks Biomedical informatics Public healthcare Employment Data mining Computer science Sensitivity analysis Pediatrics Humans
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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