Abstract
Diabetes Mellitus type 2 (DMT2) is a prevalent and increasing disease that represents a major public health challenge since it can lead to complications over the years. It is crucial to support patients, in particular, to increase knowledge regarding how to deal with DMT2 and also to develop technologies that help manage the disease. Simultaneously, there is a growing interest in recommendation systems that could be an ally in the management of diabetes mellitus, and several works in this area have already been published. A bibliometric analysis was performed to identify peer-reviewed literature from inception until November 16, 2021, regarding recommendation systems in the context of diabetes mellitus type 2. The Scopus database was used to search and analyse the characteristics of the literature retrieved. A total of 1578 documents were identified since 1985, with a higher number of publications within the research topic from 2010 onwards. “Articles” and “Medicine” were the most prevalent type of document and subject, respectively, and the country with most articles published on this topic was the United States (36%). As a result of the heightened interest in the subject, this work is the first step toward developing a more refined systematic review that considers, for example, the impact of individualized feedback in the context of a DMT2 monitoring recommendation system.
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Acknowledgments
This research work was developed under the project Food Friend – “Autonomous and easy-to-use tool for monitoring of personal food intake and personalised feedback” (ITEA 18032), co-financed by the North Regional Operational Program (NORTE 2020) under the Portugal 2020 and the European Regional Development Fund (ERDF), with the reference NORTE-01-0247-FEDER-047381. Andreia Pinto was funded by “Fundação para a Ciência e Tecnologia (FCT)”, Portugal under PhD grant number UI/BD/151485/2021. Ana Vieira was funded by FCT under PhD grant number UI/BD/151115/2021.
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Pinto, A., Martinho, D., Vieira, A., Ramalho, A., Freitas, A. (2022). Recommendation Systems in the Context of Diabetes Mellitus Type 2: A Bibliometric Analysis. In: Rocha, A., Adeli, H., Dzemyda, G., Moreira, F. (eds) Information Systems and Technologies. WorldCIST 2022. Lecture Notes in Networks and Systems, vol 468. Springer, Cham. https://doi.org/10.1007/978-3-031-04826-5_67
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