Please use this identifier to cite or link to this item: https://dspace.univ-ouargla.dz/jspui/handle/123456789/36706
Title: Artificial Intelligence Based Tuberculosis Diagnosis
Authors: Lati, Abdelhai
Hafiane, Maroua
Ferkhi, Kenza
Fellah, Aicha
Bazzine, Rania
Keywords: tuberculosis
artificial intelligence
lung X-ray
deep learning
machine learning
Issue Date: 2024
Publisher: UNIVERSITY KASDI MERBAH OUARGLA
Citation: FACULTE DES NOUVELLES TECHNOLOGIES DE L'INFORMATIQUE ET DE LA COMMUNICATION
Abstract: Tuberculosis has seen a large spread in the world and is a serious and infectious disease. We have proposed a solution for the initial diagnosis of this disease. It is a Diatub application, based on artificial intelligence and its advanced techniques of deep learning and machine learning. The method of application is by imaging the lung X-ray and lifting it to the application, after which Diatub processes the image. The result is the patient's state of health if he is infected or healthy with a percentage as this does not take long, the result can be saved so as to inform the doctor and give the final diagnosis.
URI: https://dspace.univ-ouargla.dz/jspui/handle/123456789/36706
Appears in Collections:Département d'Electronique et des Télécommunications - Master

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