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WorldCist'18 - 6th World Conference on Information Systems and Technologies

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Data Mining Techniques in Diabetes Self-management: A Systematic Map

Data mining (DM) techniques provides powerful tools to extract knowledge from a huge data offering valuable information to decision making. Medicine is one of many fields that is taking advantages from DM techniques in diabetes, cardiology, cancer and other diseases. In this paper, we investigate the use of DM techniques in diabetes, in particular in diabetes self-management (DSM). The purpose of this paper is to conduct a systematic mapping study in order to review primary studies investigating DM techniques in DSM. This mapping study aims to summarize and analyze knowledge on: 1) years and sources of DSM publications, 2) type of diabetes that took most attention, 3) DM tasks and techniques most frequently investigated, and 4) the considered functionalities. A total of 57 papers published between 2000 and April 2017 were therefore selected and analyzed with regards to four research questions. The study shows that prediction was largely the most used DM task and Neural Networks were the most frequently used technique. Moreover, T1DM is largely the type of diabetes that is most concerned by the studies so as the Prediction of blood glucose.

Touria ElIdrissi
University Mohamed V
Morocco

Ali Idri
University Mohamed V
Morocco

 

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