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<oaidc:dc xmlns:oaidc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
<dc:contributor xsi:type="unistra:Directeur">Kellenberger, Esther</dc:contributor>
<dc:coverage xsi:type="unistra:Coverage">FR</dc:coverage>
<dc:creator xsi:type="unistra:Auteur">Kaidi, Yanis</dc:creator>
<dc:date xsi:type="unistra:Date">2023-11-27</dc:date>
<dc:description xsi:type="unistra:Discipline" xml:langue="fre">Pharmacie</dc:description>
<dc:description xsi:type="unistra:Resume" xml:langue="fre">Cette thèse explore l'impact de l'intelligence artificielle (IA), en particulier du Deep Learning (DL), dans la lutte contre le cancer. En se concentrant sur le cancer du sein, la thèse examine l'utilisation de l'IA dans l'imagerie médicale, l'anatomopathologie et son rôle dans l'optimisation des traitements.</dc:description>
<dc:description xsi:type="unistra:Resume" xml:langue="fre">This thesis explores the impact of artificial intelligence (AI), specifically Deep Learning (DL), in the fight against cancer. Focusing on breast cancer, the thesis investigates the use of AI in medical imaging, anatomopathology, and its role in treatment optimization </dc:description>
<dc:format xsi:type="dcterms:IMT">PDF</dc:format>
<dc:rights xsi:type="unistra:Droits" xml:lang="fre">Accès libre</dc:rights>
<dc:identifier xsi:type="dcterms:URI">https://publication-theses.unistra.fr/public/theses_exercice/PHA/2023/2023_KAIDI_Yanis.pdf</dc:identifier>
<dc:language xsi:type="dcterms:ISO639-2">fr</dc:language>
<dc:source xsi:type="dcterms:URI">http://www.sudoc.fr/276012070</dc:source>
<dc:subject xml:langue="fre">Intelligence artificielle en médecine</dc:subject>
<dc:subject xml:langue="fre">Oncologie médicale</dc:subject>
<dc:subject xml:langue="fre">Cancer du sein</dc:subject>
<dc:subject xml:langue="fre">Informatique médicale Dissertation universitaire</dc:subject>
<dc:subject xml:langue="fre">Oncologie</dc:subject>
<dc:subject xml:langue="fre">IA</dc:subject>
<dc:subject xml:langue="fre">Intelligence Artificielle</dc:subject>
<dc:subject xml:langue="fre">Deep Learning</dc:subject>
<dc:subject xml:langue="fre">Cancer du sein</dc:subject>
<dc:subject xml:langue="fre">Drug Development</dc:subject>
<dc:subject xml:langue="fre">Radiologie</dc:subject>
<dc:subject xml:langue="fre">Anatomopathologie</dc:subject>
<dc:subject xml:langue="fre">Oncology</dc:subject>
<dc:subject xml:langue="fre">AI</dc:subject>
<dc:subject xml:langue="fre">Artificial intelligence</dc:subject>
<dc:subject xml:langue="fre">Deep Learning</dc:subject>
<dc:subject xml:langue="fre">Breast Cancer</dc:subject>
<dc:subject xml:langue="fre">Drug Development</dc:subject>
<dc:subject xml:langue="fre">Radiology</dc:subject>
<dc:subject xml:langue="fre">Pathology</dc:subject>
<dc:subject xml:langue="fre">615</dc:subject>
<dc:title xsi:type="unistra:Titre" xml:lang="fre">L' utilisation de l'intelligence artificielle en oncologie:l’apprentissage profond, nouvel outil dans le diagnostic et l'optimisation des traitements</dc:title>
<dc:type xsi:type="unistra:Mention">Thèse d'exercice</dc:type>
<dc:publisher xsi:type="unistra:Composante">Faculté de pharmacie</dc:publisher>
<dc:type xsi:type="unistra:TheseExercice">These d'exercice Unistra</dc:type>
</oaidc:dc>
