Bouharati Imene, Boubendir Nasser-Eddine, Bouharati Khaoula, Laouamri Slimane
Background: Objective: Aneurysm denotes a localized increase in arterial diameter with loss of parallelism of the artery wall. Apart from the use of existing predictive models, it is difficult to precisely determine the boundaries between the aneurysmal segment and the aortic safe portions. Also, the factors favoring the development of the aneurysm are poorly defined. In this study, we propose an intelligent analysis of the individual variability of the diameter of the abdominal aorta associated with the risk factors involved. Methods: Due to the complexity and uncertainty of individual variability, an intelligent technique analysis of the abdominal variation of the diameter of the abdominal aorta is performed. In a population of 100 patients, their ages are matched to the diameter of the abdominal aorta. An artificial neural network analysis system is proposed. This is done under the MATLAB compiler. Results: After learning the network, an input-output transfer function is created and adjusted. It then becomes possible to predict the degree of the aneurysm from a random value at the input of the system. Conclusions: a subject at a certain age is likely to have an aneurysm which it is necessary to diagnose in order to foresee his risk of rupture. The majority of cases are diagnosed accidentally in the absence of a screening program.
Aneurysm, Age, Risk factors, ANN
Cite this paper
Bouharati Imene, Boubendir Nasser-Eddine, Bouharati Khaoula, Laouamri Slimane. (2021) Artificial Neural Networks Analysis of the Abdominal Aortic Aneurysm. International Journal of Biology and Biomedicine, 6, 42-45