Abstract
Blood glucose (BG) prediction system can help gestational diabetes mellitus (GDM) patient to improve the BG control with managing their dietary intake based on healthy food. Many techniques have been developed to deal with blood glucose prediction, especially those for recommender system. In this study, we conduct a systematic mapping study to investigate recent research about BG prediction in recommender systems. This study describes an overview of research (2014-2018) about BG prediction techniques that has been used for BG recommender system. As results, 25 studies concerning BG prediction in recommender system were selected. We observed that although there is numerous studies published, only a few studies took serious discussion about techniques used to incorporate the BG algorithms. Our result highlighted that only one study discusses hybrid filtering technique in BG recommender system for GDM even though it has an ability to learn from experience and to improve prediction performance. We hope that this study will encourage researchers to consider not only machine learning and artificial intelligent techniques but also hybrid filtering technique for BG recommender system in the future research.
Highlights
Diabetes is one of the commonest chronic medical conditions, influencing around 347 million adults worldwide [1]
There is a high number of studies on the machine learning techniques whereas only one study contributed on the hybrid filtering technique for Blood glucose (BG) recommender system in 2017
There are exist so many technique for recommender system but we do not know which one is the most appropriate for BG recommender system. Until recently this has not been the case in BG recommender system for patients with gestational diabetes mellitus (GDM) since most of the studies discussed about BG recommender for diabetes
Summary
Diabetes is one of the commonest chronic medical conditions, influencing around 347 million adults worldwide [1]. Diabetes management should avoid acute and long-term complications that can be responsible for premature death and disability. The influence of diabetes is developing with 347 million people at present influenced worldwide and numbers anticipated to increment to 552 million by 2030 [1]. Gestational diabetes mellitus (GDM) is frequently described as glucose intolerance for pregnancy women. GDM have an impact for long term metabolism consequences for the mother and children from the pregnancy such as increased risk of obesity [5]. Pregnancy women should maintain normal BG levels to prevent adverse pregnancy outcomes and to break the cycle of transmission of metabolic disease to children [6]
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