Artificial neural network approach to detect COVID-19 disease from X-ray images
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Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
Mohamed Boudiaf University of M'sila
Abstract
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.
Description
Keywords
artificial neural networks, COVID-19 detection, chest X-ray images, deep learning techniques, intelligent diagnostic tools, dataset, infected cases, non-infected cases, accuracy, reliability, innovations, patient care, MEDICINE::Microbiology, immunology, infectious diseases, artificial intelligence, global health challenges