Handling Uncertainty in a Medical Study of Dietary Intake During Pregnancy

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.

• Type: Journal
• Year: 2002
• Where: SOFTWARE
• Authors: Adele H. Marshall, David A. Bell, Roy Sterritt
• Keywords: Analysis, Applied Computing, Bayesian Belief Networks, Birth Weight, SOFTWARE 2002