Glycaemic index prediction: a pilot study of data linkage challenges and the application of machine learning

Jingyuan Li, Ognjen Arandelovic

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

6 Citations (Scopus)

Abstract

The glycaemic index (GI) is widely used to characterize the effect that a food has on blood glucose which is of major importance to diabetic individuals as well as the general population at large. At present, its applicability is severely limited by the labour involved in its measurement and the lack of understanding about how different foods interact to produce the GI of the meal comprising them. In this pilot study we examine if readily available biochemical properties of food scan be used to predict their GI, thus opening possibilities for practicable use of the GI in the management of blood glucose in everyday life. We also examine practical challenges in the cross-linking of food information sources collected by different organizations, and highlight the need for the development of a universal standard which would facilitate automatic and error free data integration.
Original languageEnglish
Title of host publication2017 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)
PublisherIEEE
Pages357-360
ISBN (Electronic)9781509041794, 9781509041800
DOIs
Publication statusPublished - 18 Feb 2017
EventBHI-2017 International Conference on Biomedical and Health Informatics - Rosen Plaza Hotel, Orlando, United States
Duration: 16 Feb 201719 Feb 2017
Conference number: 4
http://bhi.embs.org/2017/

Conference

ConferenceBHI-2017 International Conference on Biomedical and Health Informatics
Abbreviated titleBHI
Country/TerritoryUnited States
CityOrlando
Period16/02/1719/02/17
Internet address

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