Please use this identifier to cite or link to this item: https://dspace.univ-ouargla.dz/jspui/handle/123456789/36706
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dc.contributor.authorLati, Abdelhai-
dc.contributor.authorHafiane, Maroua-
dc.contributor.authorFerkhi, Kenza-
dc.contributor.authorFellah, Aicha-
dc.contributor.authorBazzine, Rania-
dc.date.accessioned2024-09-17T10:09:24Z-
dc.date.available2024-09-17T10:09:24Z-
dc.date.issued2024-
dc.identifier.citationFACULTE DES NOUVELLES TECHNOLOGIES DE L'INFORMATIQUE ET DE LA COMMUNICATIONen_US
dc.identifier.urihttps://dspace.univ-ouargla.dz/jspui/handle/123456789/36706-
dc.description.abstractTuberculosis 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.en_US
dc.language.isoenen_US
dc.publisherUNIVERSITY KASDI MERBAH OUARGLAen_US
dc.subjecttuberculosisen_US
dc.subjectartificial intelligenceen_US
dc.subjectlung X-rayen_US
dc.subjectdeep learningen_US
dc.subjectmachine learningen_US
dc.titleArtificial Intelligence Based Tuberculosis Diagnosisen_US
dc.typeThesisen_US
Appears in Collections:Département d'Electronique et des Télécommunications - Master

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