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

Wenxiu Xie; Ruoyao Ding; Jun Yan; Yingying Qu

doi:10.1155/2018/9163160

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

Wenxiu Xie, Ruoyao Ding, Jun Yan, Yingying Qu

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

15 Citations (Scopus)

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. © 2018 Wenxiu Xie et al.

Original language	English
Article number	9163160
Journal	Wireless Communications and Mobile Computing
Volume	2018
DOIs	https://doi.org/10.1155/2018/9163160
Publication status	Published - 2018
Externally published	Yes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to <a href="mailto:[email protected]">[email protected]</a>.

Funding

The work was substantially supported by a grant from the National Natural Science Foundation of China (no. 61772146), the Science and Technology Plan of Guangzhou (no. 201804010296), the Innovative School Project in Higher Education of Guangdong Province (no. YQ2015062), and Scientific Research Innovation Team in Department of Education of Guangdong Province (no. 2017KCXTD013).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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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. {\textcopyright} 2018 Wenxiu Xie et al.",

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AU - Ding, Ruoyao

AU - Yan, Jun

AU - Qu, Yingying

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AB - 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. © 2018 Wenxiu Xie et al.

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DO - 10.1155/2018/9163160

M3 - RGC 21 - Publication in refereed journal

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M1 - 9163160

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

Abstract

Bibliographical note

Funding

UN SDGs

Publisher's Copyright Statement

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