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Please use this identifier to cite or link to this item: https://repository.esi-sba.dz/jspui/handle/123456789/377
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dc.contributor.authorAISSIOUENE, MAhrez-
dc.contributor.authorBOUKABRINE, FAycal Amine-
dc.date.accessioned2022-11-14T07:18:05Z-
dc.date.available2022-11-14T07:18:05Z-
dc.date.issued2022-
dc.identifier.urihttps://repository.esi-sba.dz/jspui/handle/123456789/377-
dc.descriptionEncadreur : Mme Naoum Hanaeen_US
dc.description.abstractA few decades ago, the discipline of Artificial Intelligence (AI) was born within computer science. it has implemented paradigms that have proven themselves in countless computer-aided projects. In fact, AI is ubiquitous in various areas of our lives. Among the fields in which the use of AI has broken through, health. Indeed, the tools offered by this paradigm bring a great help to the field of medicine, in particular, to aid in medical diagnosis, in particular, Artificial Neural Networks. The influence of AI is therefore increasing every day in the medical field and assists doctors of different specialties in their daily professional mission. Because of AI, many medical diagnostic aid systems have been proposed treating different types of diseases. We are interested in the present project in medical diagnostic aid systems using recent RNA models, in particular, those that perform disease recognition through X-ray image type data. Several works exist in the literature in this field faced with the aid to the diagnosis of various diseases, in particular, the recognition of the disease of osteoporosis, the detection of lung cancer, the detection of breast cancer, the recognition of cancers brain, etc. Not only that, due to the global pandemic situation that the world has been experiencing since the year 2020, AI has also been applied, and successfully, to the diagnosis of Covid-19 disease. The present work provides a literature review of recent research work on pattern recognition systems using deep learning Artificial Neural Networks (ANN) for the detection of osteoporosis disease, breast cancer disease, and CoronaVirus disease (COVID-19). *** Il y a quelques d´ec´enies, la discipline de l’Intelligence Artificielle (IA) est n´ee au sein des sciences informatiques. Elle a mis en place des paradigmes qui ont fait leurs preuves dans d’innombrables projets assist´es par ordinateur. En fait, l’IA est omnipr´esente dans des domaines diverses de notre vie. Parmis les domaines auxquels a perc´e l’utilisation de l’IA, la sant´e. En effet, les outils qu’offre ce paradigme apporte une grande aide au domaine de la medecine, notamment, ´a l’aide au diagnostique m´edical, en particulier, les R´eseaux de Neurone Artificiels. L’influence de l’IA de ce fait augmente chaque jour dans le cadre m´edical et assiste les medecins de diff´erentes sp´ecialit´es dans leur mission professionelle au quotidien. Grace a l’IA, beaucoup de systemes d’aide au diagnostique m´edical ont ´et´e propos´e traitant diff´erents types de maladies. On s’interesse dans le pr´esent projet aux syst´emes d’aide au diagnostique m´edical utilisant les mod´eles de RNAs r´ecents, en particulier, ceux qui effectuent la reconnaissance de la maladie ´a travers des donn´ees de types images radiographiques. Plusieurs travaux existent dans la litterature dans ce domaine faisat face ´a l’aide au diagnostique de maladies diverses, notamment, la reconnaissance de la maladie d’osp´eoporose, la detection du cancer des poumons, la detection du cancer du sein, la reconnaissance de cancers du cerveau, etc. Pas seulement, en raison de la situation mondiale de pand´emie que connait le monde depuis l’an 2020, l’IA a ´egalement ´et´e appliqu´ee, et avec succ´es, au diagnostique de la maladie Covid-19. Le pr´esent travail apporte une revue de la litt´erature de travaux de recherche r´ecents sur les syst´emes de reconnaissance de formes utilisant les R´eseaux de Neurones Artificiels (RNA) ´a apprentissage profond pour la d´etection de la maladie d’ost´eoporose, la maladie du cancer du sein, et la maladie du CoronaVirus (COVID-19).en_US
dc.language.isoenen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectArtificial Neural Networksen_US
dc.titleRéseaux neuronaux a apprentissage profond au service de la classification d’images radiographiques.en_US
dc.typeThesisen_US
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