Smart Web application to support medical diagnosis decision making / Faycal Zetoutou  

Public ISBD Titre : Smart Web application to support medical diagnosis decision making Type de document : texte imprimé Auteurs : Faycal Zetoutou, Auteur ; Zakaria Nedjem Eddine Mahdadi, Auteur ; Ferradji,Mohamed Abderraouf, Directeur de thèse Année de publication : 2023 Importance : 1 vol (64 f .) Format : 29cm Langues : Français (fre) Catégories : Thèses & Mémoires:Informatique Mots-clés : Artificial Intelligence Machine Learning Index. décimale : 004 Informatique Résumé : Despite the impressive research results related to the application of artificial intelligence in the medical field, its exploitation in the real clinical setting, especially in diagnostic decision making, remains very limited. Therefore, our objective in this work is to develop a smart web application that supports medical professionals in making efficient diagnostic decisions. Based on deep learning techniques and intelligent prediction models, the proposed system provides doctors with accurate predictions that aim to promote their medical diagnostic skills and enhance the patient healthcare quality. Furthermore, this smart web application highlights the importance of collaboration in medical diagnosis while facilitating efficient interaction and knowledge sharing among medical professionals. Côte titre : MAI/0711 En ligne : https://drive.google.com/file/d/1ovs5Z4fZ6gJD2GjmSnxvFi99F4mjm4Rc/view?usp=drive [...] Format de la ressource électronique : pdf Smart Web application to support medical diagnosis decision making [texte imprimé] / Faycal Zetoutou, Auteur ; Zakaria Nedjem Eddine Mahdadi, Auteur ; Ferradji,Mohamed Abderraouf, Directeur de thèse . - 2023 . - 1 vol (64 f .) ; 29cm. Langues : Français (fre) Catégories : Thèses & Mémoires:Informatique Mots-clés : Artificial Intelligence Machine Learning Index. décimale : 004 Informatique Résumé : Despite the impressive research results related to the application of artificial intelligence in the medical field, its exploitation in the real clinical setting, especially in diagnostic decision making, remains very limited. Therefore, our objective in this work is to develop a smart web application that supports medical professionals in making efficient diagnostic decisions. Based on deep learning techniques and intelligent prediction models, the proposed system provides doctors with accurate predictions that aim to promote their medical diagnostic skills and enhance the patient healthcare quality. Furthermore, this smart web application highlights the importance of collaboration in medical diagnosis while facilitating efficient interaction and knowledge sharing among medical professionals. Côte titre : MAI/0711 En ligne : https://drive.google.com/file/d/1ovs5Z4fZ6gJD2GjmSnxvFi99F4mjm4Rc/view?usp=drive [...] Format de la ressource électronique : pdf

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
MAI/0711	MAI/0711	Mémoire	Bibliothéque des sciences	Anglais	Disponible Disponible

---

1 (1 - 1 / 1)