Handling uncertainty in a medical study of dietary intake during pregnancy

Alan Marshall, D. Bell, R. Sterritt

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish
Title of host publicationSoft-Ware 2002: Computing in an Imperfect World
Pages206-216
Number of pages11
Volume2311
DOIs
Publication statusPublished - 2002

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume2311
ISSN (Electronic)1611-3349

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  • Cite this

    Marshall, A., Bell, D., & Sterritt, R. (2002). Handling uncertainty in a medical study of dietary intake during pregnancy. In Soft-Ware 2002: Computing in an Imperfect World (Vol. 2311, pp. 206-216). (Lecture Notes in Computer Science ; Vol. 2311). https://doi.org/10.1007/3-540-46019-5_16