Abstract
Reuse past experiences in solving new problems is common in the everyday lives, since it is well obvious and legitimate that similar problems have similar solutions and we are often confronted with a problem already met. The case-based reasoning (CBR) as a powerful design methodology of intelligent systems can be strengthened in the different stages of process by techniques for optimization. In a previous work [10], an approach guided by case-based reasoning based on retrieval by fuzzy decision tree has been proposed. In this paper, we propose a medical decision support system to assist physicians by adapting monitoring plans. The case-based reasoning process involves through several steps, we are interested in the adaptation phase which is to reuse totally or partially a solution of the selected case to solve the new problem. FUZZY DTA offers a medical decision making support system using a fuzzy reasoning for diabetes surveillance plans.
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Benamina, M., Atmani, B., Benbelkacem, S., Mansoul, A. (2019). Fuzzy Adaptation of Surveillance Plans of Patients with Diabetes. In: Alfaries, A., Mengash, H., Yasar, A., Shakshuki, E. (eds) Advances in Data Science, Cyber Security and IT Applications. ICC 2019. Communications in Computer and Information Science, vol 1098. Springer, Cham. https://doi.org/10.1007/978-3-030-36368-0_11
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