Diabetes Mellitus Type II (T2D) is a Chronic Disease and is the most common type of Diabetes in the world, responsible for 95% of all Diabetes patients. T2D is a very complex disease and requires a large amount of self-management from the patient in order to maintain a healthy and threat-free lifestyle. Therefore, we develop in this paper a data analytics solution to assist in the self-management of T2D patients through several methods consisting of a rule-based system, anomaly detection, and threat forecasting.

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Keywords Anomaly Detection, Artificial Intelligence, Chronic Diseases, Diabetes, Forecasting
Persistent URL dx.doi.org/10.1109/WCNC.2019.8885802
Conference 2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
Arab, K. (Kareem), Bouida, Z. (Zied), & Ibnkahla, M. (2019). Artificial Intelligence for Diabetes Mellitus Type II: Forecasting and Anomaly Detection. In IEEE Wireless Communications and Networking Conference, WCNC. doi:10.1109/WCNC.2019.8885802