Title: Architecture of a decision support system based on big data for monitoring type 2 diabetics

Authors: Boudhir Anouar Abdelhakim; Ben Ahmed Mohamed; Fellaji Soumaya

Addresses: List Laboratory, Computer Sciences Department, Faculty of Sciences and Techniques, Abdelmalek Essaâdi University, Ancienne Route de l'Aéroport, Km 10, Ziaten., BP: 416. Tangier, Morocco ' List Laboratory, Computer Sciences Department, Faculty of Sciences and Techniques, Abdelmalek Essaâdi University, Ancienne Route de l'Aéroport, Km 10, Ziaten., BP: 416. Tangier, Morocco ' Fsjest Faculty, University Abdelmalek Essaâdi, Tangier, Morocco

Abstract: Type 2 diabetes is one of chronic diseases that require continuous and real-time monitoring to prevent the occurrence of complications. First, the doctor must have information about the patient's daily life (vital signs, stress, sedentary lifestyle, physical activities, nutrition, etc.). Secondly, the prescribed treatment must be evaluated each time to test the validity of the diagnosis. To achieve this goal, a decision support system based on big data mining technology must be designed in order to have a centralised knowledge of diabetics. This system will improve the quality of monitoring and treatment from the different data collected. Thus, this paper presents an architecture of a decision support system allowing doctors to monitor the health status of their patients, based on data collected from different resources, in order to enrich the knowledge database and prescribe new treatments based on similar cases and experiences of doctors and patients belonging to this system.

Keywords: big data; analytics; Hadoop; healthcare; diabetes.

DOI: 10.1504/IJIE.2019.101127

International Journal of Intelligent Enterprise, 2019 Vol.6 No.2/3/4, pp.204 - 216

Received: 18 Jan 2018
Accepted: 25 Sep 2018
Published online: 24 Jul 2019 *

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