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Systematic map and review of predictive techniques in diabetes self-management

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  • EL Idrissi, Touria
  • Idri, Ali
  • Bakkoury, Zohra

Abstract

Data mining (DM) provides powerful tools to extract knowledge from large volumes of data offering valuable information to decision making. The extracted knowledge can be used for predictive and/or descriptive purposes. DM has been successfully used in different subfields of eHealth such us cardiology, oncology and endocrinology. This paper deals with the use of DM predictive techniques in diabetes self-management (DSM).To the best of our knowledge, neither a systematic map nor a systematic review have yet been performed with a focus on the use of DM predictive techniques in DSM. Thus, the aim of this study is to classify and review primary studies investigating DM predictive techniques in DSM by summarizing and analyzing knowledge with respect to: year and source of publication, type of diabetes, clinical tasks, DM predictive techniques, and the performance of the predictive techniques used. A total of 38 papers published between 2000 and April 2017 were therefore selected and analyzed accordingly to address six research questions. The results show that Type 1 Diabetes Mellitus (T1DM) is largely the type of diabetes that is most concerned by the studies and the prediction of blood glucose is the most investigated clinical task. Moreover, artificial neural networks were the most frequently used predictive technique which along with autogressive models, yield highest accuracy rates.

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  • EL Idrissi, Touria & Idri, Ali & Bakkoury, Zohra, 2019. "Systematic map and review of predictive techniques in diabetes self-management," International Journal of Information Management, Elsevier, vol. 46(C), pages 263-277.
    • Handle: RePEc:eee:ininma:v:46:y:2019:i:c:p:263-277
    DOI: 10.1016/j.ijinfomgt.2018.09.011
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    References listed on IDEAS

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    1. Zhang, Yao & Li, Xiaoming, 2017. "Uses of information and communication technologies in HIV self-management: A systematic review of global literature," International Journal of Information Management, Elsevier, vol. 37(2), pages 75-83.
    2. Pinho, Cláudia & Franco, Mário & Mendes, Luis, 2018. "Web portals as tools to support information management in higher education institutions: A systematic literature review," International Journal of Information Management, Elsevier, vol. 41(C), pages 80-92.
    3. Zahedi, Mansooreh & Shahin, Mojtaba & Ali Babar, Muhammad, 2016. "A systematic review of knowledge sharing challenges and practices in global software development," International Journal of Information Management, Elsevier, vol. 36(6), pages 995-1019.
    4. Balaid, Ali & Abd Rozan, Mohd Zaidi & Hikmi, Syed Norris & Memon, Jamshed, 2016. "Knowledge maps: A systematic literature review and directions for future research," International Journal of Information Management, Elsevier, vol. 36(3), pages 451-475.
    5. Sultan, Nabil, 2015. "Reflective thoughts on the potential and challenges of wearable technology for healthcare provision and medical education," International Journal of Information Management, Elsevier, vol. 35(5), pages 521-526.
    6. Rekik, Rim & Kallel, Ilhem & Casillas, Jorge & Alimi, Adel M., 2018. "Assessing web sites quality: A systematic literature review by text and association rules mining," International Journal of Information Management, Elsevier, vol. 38(1), pages 201-216.
    7. Busalim, Abdelsalam H. & Hussin, Ab Razak Che, 2016. "Understanding social commerce: A systematic literature review and directions for further research," International Journal of Information Management, Elsevier, vol. 36(6), pages 1075-1088.
    8. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    9. Mohan, Kunal & Ahlemann, Frederik, 2013. "Understanding acceptance of information system development and management methodologies by actual users: A review and assessment of existing literature," International Journal of Information Management, Elsevier, vol. 33(5), pages 831-839.
    10. Nidhra, Srinivas & Yanamadala, Muralidhar & Afzal, Wasif & Torkar, Richard, 2013. "Knowledge transfer challenges and mitigation strategies in global software development—A systematic literature review and industrial validation," International Journal of Information Management, Elsevier, vol. 33(2), pages 333-355.
    11. Iden, Jon & Eikebrokk, Tom Roar, 2013. "Implementing IT Service Management: A systematic literature review," International Journal of Information Management, Elsevier, vol. 33(3), pages 512-523.
    12. Costa, Eric & Soares, António Lucas & de Sousa, Jorge Pinho, 2016. "Information, knowledge and collaboration management in the internationalisation of SMEs: A systematic literature review," International Journal of Information Management, Elsevier, vol. 36(4), pages 557-569.
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    3. Nadine Ostern & Guido Perscheid & Caroline Reelitz & Jürgen Moormann, 2021. "Keeping pace with the healthcare transformation: a literature review and research agenda for a new decade of health information systems research," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(4), pages 901-921, December.

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