Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Hajer Ayadi"'
Publikováno v:
Diagnostics, Vol 14, Iss 11, p 1204 (2024)
In recent years, Convolutional Neural Network (CNN) models have demonstrated notable advancements in various domains such as image classification and Natural Language Processing (NLP). Despite their success in image classification tasks, their potent
Externí odkaz:
https://doaj.org/article/b73f3c8f63134fc8ad78fd5b86355c5a
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783031333767
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6500a6f51b6446580442d9f1df68374a
https://doi.org/10.1007/978-3-031-33377-4_26
https://doi.org/10.1007/978-3-031-33377-4_26
Publikováno v:
Artificial Intelligence in Medicine. 140:102551
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::579d127a0575f3a11990268b0be470d5
https://doi.org/10.1016/j.artmed.2023.102551
https://doi.org/10.1016/j.artmed.2023.102551
Autor:
Mouhamed Moustapha Hamoudi, Nesrin Kallel, Samy Kammoun, Walid Feki, Hajer Ayadi, R. Khemakhem, Med Lemine Sidi Oumare, Rahma Gargouri, Ilhem Yangui
Publikováno v:
Lung cancer.
Introduction: The coronavirus disease (COVID-19) continues to pose a serious health threat in 2021 with several impacts, especially for patients being managed for lung cancer. The aim of our work is to study the psychological and health care impact o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf6594b4d274c069b355ece391de0457
https://doi.org/10.1183/13993003.congress-2021.pa3847
https://doi.org/10.1183/13993003.congress-2021.pa3847
This collection of essays aims to revise genre theory and studies. Authors in this volume present and discuss different literary genres in transition. They investigate genre hybridization, transformation, reconciliation and evolution. Therefore, the
Autor:
Hajer Ayadi, Mouna Torjmen–Khemamkhem
Publikováno v:
Digital Health in Focus of Predictive, Preventive and Personalised Medicine ISBN: 9783030498146
Facing the explosion in the amount of medical images, the image indexing and the retrieval systems have seen an evolution to provide access to biomedical literature and satisfy the user information needs. Hence, several context-based medical image re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::435f9bc8358825731d8b94077ef22dbd
https://doi.org/10.1007/978-3-030-49815-3_9
https://doi.org/10.1007/978-3-030-49815-3_9
Publikováno v:
Journal of the Association for Information Science and Technology. 69:1095-1108
One of the main challenges in medical image retrieval is the increasing volume of image data, which render it difficult for domain experts to find relevant information from large data sets. Effective and efficient medical image retrieval systems are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a7f80d755a41ffa37575a71fe08e3bb1
https://doi.org/10.1002/asi.24045
https://doi.org/10.1002/asi.24045
Publikováno v:
Journal of the Association for Information Science and Technology. 68:1323-1334
The abundance of medical resources has encouraged the development of systems that allow for efficient searches of information in large medical image data sets. State-of-the-art image retrieval models are classified into three categories: content-base
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ebb6a0481752f66b0cae324a3232e93
https://doi.org/10.1002/asi.23772
https://doi.org/10.1002/asi.23772
Publikováno v:
HEALTHINF
With the proliferation of digital imaging data in hospitals, the amount of medical images is increasing rapidly. Thus, the need for efficient retrieval systems, to find relevant information from large medical datasets, becomes high. The Convolutional
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf9a7f7f41bc0953770f16eb0ad35706
https://doi.org/10.5220/0007355400780087
https://doi.org/10.5220/0007355400780087
Autor:
Ahmed Rebai, Neila Belghith-Mahfoudh, Hajer Ayadi, Achraf Ben Youssef, Ghada Ben Salah, Faiza Fakhfakh, H. Ayadi, Hassen Kamoun, Amine Fourati
Publikováno v:
Mutation Research/Genetic Toxicology and Environmental Mutagenesis. 719:1-6
Cigarette smoking is a major public health problem in Tunisia as it concerns up to 30-35% of the adult population, raising important national issues on tobacco-related disease. The aim of this study was to establish whether cigarette smoking increase
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::23223307a120bb607f1a466c05822a51
https://doi.org/10.1016/j.mrgentox.2010.09.003
https://doi.org/10.1016/j.mrgentox.2010.09.003