Thèses en ligne de l'université 8 Mai 1945 Guelma

Prédiabète : Un Système de Détection et prédiction de diabète

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dc.contributor.author SAHLI, SOUHA
dc.date.accessioned 2022-10-17T07:35:41Z
dc.date.available 2022-10-17T07:35:41Z
dc.date.issued 2022
dc.identifier.uri http://dspace.univ-guelma.dz/jspui/handle/123456789/13349
dc.description.abstract Today, diabetes is one of the most common chronic diseases that can cause certain complications that can sometimes cause death. So, there is an urgent need for a prognostic tool that can help doctors detect the disease at an early stage and recommend the neces- sary lifestyle changes to stop the progression of this disease. Deep learning is an urgent need today to eliminate human effort and offer higher automation with fewer errors. In this project, a diabetes detection and prediction system is developed based on a deep lear- ning approach (ANN+GAN). Experiments conducted on the Pima data collection have given encouraging prediction results in comparison with two other machine learning approaches that we have implemented, namely: SVM and KNN. en_US
dc.language.iso fr en_US
dc.publisher université de guelma en_US
dc.subject deep learning KNN ANN en_US
dc.title Prédiabète : Un Système de Détection et prédiction de diabète en_US
dc.type Working Paper en_US


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