Communications Internationales

Permanent URI for this collectionhttps://dspace.univ-boumerdes.dz/handle/123456789/11

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Author: search.filters.author.Berrichi, Ali

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    Vision Transformer Model for Gastrointestinal Tract Diseases Classification from WCE Images
    (Institute of Electrical and Electronics Engineers, 2024) Bella, Faiza; Berrichi, Ali; Moussaoui, Abdelouahab
    Accurate disease classification utilizing endoscopic images indeed poses a significant challenge within the field of gastroenterology. This research introduces a methodology for assisting medical diagnostic procedures and detecting gastrointestinal (GI) tract diseases by categorizing features extracted from endoscopic images using Vision Transformer (ViT) models. We propose three ViT-inspired models for classifying GI tract diseases using colon images acquired through wireless capsule endoscopy (WCE). The highest achieved accuracy among our models is 97.83%. We conducted a comparative analysis with three pre-trained CNN (Convolutional Neural Network) models namely, Xception, DenseNet121, and MobileNet, alongside recent research papers to validate our findings.
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    Machine learning in the medical field: A comprehensive overview
    (Institute of Electrical and Electronics Engineers Inc, 2023) Belgacem, Ali; Khoudi, Asmaa; Boudane, Fatima; Berrichi, Ali
    Machine learning utilization in medicine has increased interest over the last few years. With its impressive results in treating diseases and medical conditions, it will be important to understand and analyze how the scientific community has used it. Thus, opening up space for new research and opportunities in medicine. The objective of this study is to review the literature on machine learning applications in the medical sector. Therefore, we conducted an extensive research by reviewing recent studies and surveys on machine-learning health solutions. As a result, we offer, in this paper, a fresh study affirming the foundations and necessities of a machine learning application in the medical field. We also provide a breakdown of current research trends, which highlights future research opportunities.
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    Heuristics to maximize system availability on parallel machine scheduling problem
    (IEEE, 2015) Khoudi, Asmaa; Berrichi, Ali; Yalaoui, Farouk