Handling Uncertainty in a Medical Study of Dietary Intake during Pregnancy

AH Marshall; DA Bell; R Sterritt

doi:10.1007/3-540-46019-5_16

Handling Uncertainty in a Medical Study of Dietary Intake during Pregnancy

AH Marshall, DA Bell, R Sterritt

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper is concerned with handling uncertainty as part of the analysis of data from a medical study. The study is investigating connections between the birth weight of babies and the dietary intake of their mothers. Bayesian belief networks were used in the analysis. Their perceived benefits include (i) an ability to represent the evidence emerging from the evolving study, dealing effectively with the inherent uncertainty involved; (ii) providing a way of representing evidence graphically to facilitate analysis and communication with clinicians; (iii) helping in the exploration of the data to reveal undiscovered knowledge; and (iv) providing a means of developing an expert system application.

Original language	English
Title of host publication	Unknown Host Publication
Place of Publication	Berlin
Publisher	Springer
Pages	206-216
Number of pages	11
ISBN (Print)	3-540-43481-X
DOIs	https://doi.org/10.1007/3-540-46019-5_16
Publication status	Published (in print/issue) - Apr 2002
Event	Soft-ware 2002: Computing in an Imperfect World - Belfast, Northern Ireland Duration: 1 Apr 2002 → …

Conference

Conference	Soft-ware 2002: Computing in an Imperfect World
Period	1/04/02 → …

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10.1007/3-540-46019-5_16

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title = "Handling Uncertainty in a Medical Study of Dietary Intake during Pregnancy",

abstract = "This paper is concerned with handling uncertainty as part of the analysis of data from a medical study. The study is investigating connections between the birth weight of babies and the dietary intake of their mothers. Bayesian belief networks were used in the analysis. Their perceived benefits include (i) an ability to represent the evidence emerging from the evolving study, dealing effectively with the inherent uncertainty involved; (ii) providing a way of representing evidence graphically to facilitate analysis and communication with clinicians; (iii) helping in the exploration of the data to reveal undiscovered knowledge; and (iv) providing a means of developing an expert system application.",

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AB - This paper is concerned with handling uncertainty as part of the analysis of data from a medical study. The study is investigating connections between the birth weight of babies and the dietary intake of their mothers. Bayesian belief networks were used in the analysis. Their perceived benefits include (i) an ability to represent the evidence emerging from the evolving study, dealing effectively with the inherent uncertainty involved; (ii) providing a way of representing evidence graphically to facilitate analysis and communication with clinicians; (iii) helping in the exploration of the data to reveal undiscovered knowledge; and (iv) providing a means of developing an expert system application.

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T2 - Soft-ware 2002: Computing in an Imperfect World

Y2 - 1 April 2002

ER -

Handling Uncertainty in a Medical Study of Dietary Intake during Pregnancy

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