Educational Tool for Diabetic Patients Based on Causal Probabilistic Networks

Authors:
M. Elena Hernando;Enrique J. Gómez;Francisco del Pozo
Affiliations:
-;-;-
Venue:
AIME '01 Proceedings of the 8th Conference on AI in Medicine in Europe: Artificial Intelligence Medicine
Year:
2001

Citing 2
Cited 1

Probabilistic reasoning in intelligent systems: networks of plausible inference

Probabilistic reasoning in intelligent systems: networks of plausible inference
A user-centered cooperative information system for medical imaging diagnosis

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Preventing knowledge transfer errors: Probabilistic decision support systems through the users' eyes

International Journal of Approximate Reasoning

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Abstract

EduDIABNET is an educational tool based on a physiological model that allows simulation and interpretation of the effect of therapeutic actions on the 24-hour blood glucose profile. The system aims to help patients to better their understanding of diabetes self-management and to provide health care professionals with an additional tool to complement the patient education. The physiological model is qualitative and is represented by a quantitative Causal Probabilistic Network. The system enables users to set model variables choosing from a group of qualitative options and presents qualitative results. The user interface has been developed using real-world graphical metaphors to hide the complexity of the physiological model and to increase system usability.