Please use this identifier to cite or link to this item: http://dspace.univ-temouchent.edu.dz/handle/123456789/2182
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMOULEBHAR, Samia-
dc.contributor.authorBENDIMERAD.M, BENDIMERAD.M-
dc.contributor.authorTAYBI, NAIMA-
dc.contributor.authorYAHLA, YAHLA-
dc.date.accessioned2024-02-13T10:31:40Z-
dc.date.available2024-02-13T10:31:40Z-
dc.date.issued2022-
dc.identifier.urihttp://dspace.univ-temouchent.edu.dz/handle/123456789/2182-
dc.description.abstractDepression is a psychological illness that occurs in many people at different ages. As part of our work, we proposed two intelligent methods based on AI to automatically diagnose depression where we automated two international tests (Beck, resilience test) and global diagnosis by artificial neural network We also performed neural classifieds of MRI images for the detection of depression. Then we used fuzzy inference systems to conclude the difference in severity of patients in the same class Finally, we programmed interfaces summarizing our proposed diagnosis The results obtained are satisfactory and demonstrate the effectiveness of our methodsen_US
dc.language.isofren_US
dc.subjectDepression, Diagnostic Automation, Beck, Resilience, RNA, SIF, MRI ven_US
dc.subjectDépression, automatisation de diagnostic, Beck, Résilience, RNA, SIF, IRMen_US
dc.titleAUTOMATISATION DU DIAGNOSTIC DE LA DEPRESSION PAR LES METHODES DE L’INTELLIGENCE ARTIFICIELLEen_US
dc.typeThesisen_US
Appears in Collections:Electronique

Files in This Item:
File Description SizeFormat 
mémoire finale.pdf2,49 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.