A Mobile‐Based Question‐Answering and Early Warning System for Assisting Diabetes Management
W Xie, R Ding, J Yan, Y Qu - Wireless Communications and …, 2018 - Wiley Online Library
W Xie, R Ding, J Yan, Y Qu
Wireless Communications and Mobile Computing, 2018•Wiley Online LibraryWith 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 …
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 …
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.
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