A Mobile-Based Question-Answering and Early Warning System for Assisting Diabetes Management

Author:

Xie Wenxiu1ORCID,Ding Ruoyao1ORCID,Yan Jun2ORCID,Qu Yingying3ORCID

Affiliation:

1. School of Information Science and Technology, Guangdong University of Foreign Studies, Guangzhou, China

2. AI Lab, Yidu Cloud (Beijing) Technology Co. Ltd., Beijing, China

3. School of Business, Guangdong University of Foreign Studies, Guangzhou, China

Abstract

With increasing demand for preventive management of chronic diseases in real time by using the Internet, interest in developing a convenient device on health management and monitoring has intensified. Unlike other chronic diseases, diabetes particularly type 2 is a lifelong chronic disease and usually requires daily health management by patients themselves. This study is to develop a mobile-based diabetes question-answering (Q&A) and early warning system named Dia-AID, assisting diabetes patients and populations at high risk. The Dia-AID system consists of three modules: a large-scale multilanguage diabetes frequently asked question repository, a multimode fusion Q&A framework, and a health data management module. A list of services including risk assessment and health early warning is provided to users for health condition monitoring. Using the diabetes frequently asked question repository as data, experiments are conducted on answer ranking and answer selection aspects. Results show that two essential methods in the system outperform baseline methods on both aspects.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

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