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 |
Files in This Item:
File | Description | Size | Format | |
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HAFIANE-FERKHI-FELLAH-BAZZINE.pdf | 1,93 MB | Adobe PDF | View/Open |
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