Please use this identifier to cite or link to this item: http://dspace.univ-temouchent.edu.dz/handle/123456789/1589
Title: Détection et iDentification De l’hépatite par les systèmes intelligents
Authors: MALLE, Aminata
ZARA, Ali Abakar
Keywords: Functional disorders of the liver, Fuzzy logic, Neural network, Genetic algorithms, Fuzzy classifier, Classical neural classifier, Selection of input variables
Issue Date: 2020
Citation: https://theses.univ-temouchent.edu.dz/opac_css/doc_num.php?explnum_id=2752
Abstract: The liver is the largest abdominal organ. It performs several vital functions. Its main role is to ensure purification, synthesis, and storage. This organ is the most exposed to toxins in the body. This can disturb its functioning and expose it to serious diseases such as liver cancer, hepatitis... Hepatitis is an inflammation of the liver. This disease is caused by several factors depending on its type. Due to its late detection, it turns into a serious form (cirrhosis, liver cancer) and can cause death. Advances in artificial intelligence in the field of medicine have made it easier today to diagnose diseases at an early stage. In our work, we have used fuzzy logic, neural networks and genetic algorithms for the detection and identification of hepatitis. We used a hepatitis database containing twenty-eight (28) input variables for the detection and identification of hepatitis and then reduced these input variables in order to reduce the complexity of the system and improve performance. The results obtained are very satisfactory and promising
URI: https://dspace.univ-temouchent.edu.dz/handle/123456789/1589
Appears in Collections:Electronique

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