(Mohamed Boudiaf University of M'sila, 2023) Hichem, Laboukhi; Abdelhakim, Benamara; Sayad, Lamri: Rapporteur
This research employs artificial neural networks, specifically deep learning techniques, to
detect COVID-19 from chest X-ray images. The study created and assessed a neural network
model using a dataset of medical images from both COVID-19 infected and non-infected
individuals. The results demonstrated the model's effectiveness in accurately distinguishing
between infected and non-infected cases, showcasing its potential as a valuable diagnostic tool for
COVID-19. The study emphasizes the necessity for ongoing research, expanding datasets, and
refining neural network models to enhance accuracy. It underscores the significant potential of
artificial intelligence and deep learning in disease diagnosis, promoting continuous collaboration
between researchers and healthcare institutions to address global health challenges.