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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Grande-Ramírez, José Roberto
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Computer Science & IT Engineering

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Intelligent fuzzy system to assess the risk of type 2 diabetes and diagnosis in marginalized regions Grande-Ramírez, José Roberto; Meza-Palacios, Ramiro; Aguilar-Lasserre, Alberto A.; Flores-Asis, Rita; Vázquez-Rodríguez, Carlos F.
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp1935-1944

Abstract

Diabetes is one of the leading causes of death in the world and continues to rise. Type 2 diabetes mellitus is a life-threatening chronic degenerative disease if not appropriately controlled; risk factors and ineffective diagnosis continue to increase its prevalence. This study proposes an intelligent fuzzy system to make a diagnosis and predict the risk of developing type 2 diabetes mellitus. The system consists of two models; the R-T2DM model estimates if a person is at risk of developing type 2 diabetes mellitus. The DT2DM model is based on two systems: the symptomatology system estimates the level of symptoms the patient has, and the diagnosis system diagnoses type 2 diabetes mellitus. The results of this research were compared with those estimated by the team of doctors, and it was observed that the R-T2DM model obtained a success rate of 90.3%. The D-T2DM model got a success rate of 88.3% for the symptomatology system and 95.5% for the diagnosis system. The model developed in this study is focused on being applied in economically marginalized geographic areas of Mexico to improve the patient's quality of life.
Co-Authors Aguilar-Lasserre, Alberto A. Flores-Asis, Rita Meza-Palacios, Ramiro Vázquez-Rodríguez, Carlos F.