Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Sylvain Berlemont"'
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 3, Iss 1, Pp 243-262 (2021)
Deep learning methods are widely used for medical applications to assist medical doctors in their daily routine. While performances reach expert’s level, interpretability (highlighting how and what a trained model learned and why it makes a specifi
Externí odkaz:
https://doaj.org/article/34908cc7e93b4ebe90ddcc0559c18805
Autor:
Roxane Bunod, Mélanie Lubrano, Antoine Pirovano, Géraldine Chotard, Emmanuelle Brasnu, Sylvain Berlemont, Antoine Labbé, Edouard Augstburger, Christophe Baudouin
Publikováno v:
Journal of Clinical Medicine, Vol 12, Iss 2, p 507 (2023)
Introduction. Glaucoma and non-arteritic anterior ischemic optic neuropathy (NAION) are optic neuropathies that can both lead to irreversible blindness. Several studies have compared optical coherence tomography angiography (OCTA) findings in glaucom
Externí odkaz:
https://doaj.org/article/93f2ba071c80406c92bcb56ba021d8a4
Autor:
Charles Lépine, Paul Klein, Thibault Voron, Marion Mandavit, Dominique Berrebi, Sophie Outh-Gauer, Hélène Péré, Louis Tournier, Franck Pagès, Eric Tartour, Thomas Le Meur, Sylvain Berlemont, Natacha Teissier, Mathilde Carlevan, Nicolas Leboulanger, Louise Galmiche, Cécile Badoual
Publikováno v:
Frontiers in Oncology, Vol 11 (2021)
Juvenile-onset recurrent respiratory papillomatosis (JoRRP) is a condition characterized by the repeated growth of benign exophytic papilloma in the respiratory tract. The course of the disease remains unpredictable: some children experience minor sy
Externí odkaz:
https://doaj.org/article/68d8a6bb38f544fa9e64d9c7c45ca7d7
Autor:
Alexandra Miere, Thomas Le Meur, Karen Bitton, Carlotta Pallone, Oudy Semoun, Vittorio Capuano, Donato Colantuono, Kawther Taibouni, Yasmina Chenoune, Polina Astroz, Sylvain Berlemont, Eric Petit, Eric Souied
Publikováno v:
Journal of Clinical Medicine, Vol 9, Iss 10, p 3303 (2020)
Background. In recent years, deep learning has been increasingly applied to a vast array of ophthalmological diseases. Inherited retinal diseases (IRD) are rare genetic conditions with a distinctive phenotype on fundus autofluorescence imaging (FAF).
Externí odkaz:
https://doaj.org/article/f29b6e8857534a8eb5417666e9e48163
Autor:
Mélanie Lubrano, Tristan Lazard, Guillaume Balezo, Yaëlle Bellahsen-Harrar, Cécile Badoual, Sylvain Berlemont, Thomas Walter
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031250811
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1cb9f1f10e68df9451405c3a51df7433
https://doi.org/10.1007/978-3-031-25082-8_27
https://doi.org/10.1007/978-3-031-25082-8_27
Diagnosis of head and neck squamous dysplasia and carcinomas is critical for patient care, cure and follow-up. It can be challenging, especially for intraepithelial lesions. Even though the last WHO classification simplified the grading of dysplasia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eaf30671a738f30b538520e310b55803
https://doi.org/10.1101/2022.12.21.521392
https://doi.org/10.1101/2022.12.21.521392
Autor:
Mélanie Lubrano, Tristan Lazard, Guillaume Balezo, Yaëlle Bellahsen-Harrar, Cécile Badoual, Sylvain Berlemont, Thomas Walter
In computational pathology, predictive models from Whole Slide Images (WSI) mostly rely on Multiple Instance Learning (MIL), where the WSI are represented as a bag of tiles, each of which is encoded by a Neural Network (NN). Slide-level predictions a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b4590726e786637f1a489c5eda299bc3
https://doi.org/10.1101/2022.01.14.476330
https://doi.org/10.1101/2022.01.14.476330
Publikováno v:
Medical Image Analysis
Medical Image Analysis, Elsevier, 2021, 73, pp.102167. ⟨10.1016/j.media.2021.102167⟩
Medical Image Analysis, Elsevier, 2021, 73, pp.102167. ⟨10.1016/j.media.2021.102167⟩
International audience; While pap test is the most common diagnosis methods for cervical cancer, their results are highly dependent on the ability of the cytotechnicians to detect abnormal cells on the smears using brightfield microscopy. In this pap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2d4579a5617f6f03b418dc8836d9605
https://hal.telecom-paris.fr/hal-03324485
https://hal.telecom-paris.fr/hal-03324485
Publikováno v:
Machine Learning and Knowledge Extraction
Machine Learning and Knowledge Extraction, MDPI, 2021, 3 (1), pp.243-262. ⟨10.3390/make3010012⟩
Machine Learning and Knowledge Extraction, Vol 3, Iss 12, Pp 243-262 (2021)
Volume 3
Issue 1
Pages 12-262
Machine Learning and Knowledge Extraction, MDPI, 2021, 3 (1), pp.243-262. ⟨10.3390/make3010012⟩
Machine Learning and Knowledge Extraction, Vol 3, Iss 12, Pp 243-262 (2021)
Volume 3
Issue 1
Pages 12-262
International audience; Deep learning methods are widely used for medical applications to assist medical doctors in their daily routine. While performances reach expert's level, interpretability (highlighting how and what a trained model learned and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::58f52712968014a68cd34517c6758163
https://hal.telecom-paris.fr/hal-03324456
https://hal.telecom-paris.fr/hal-03324456
Publikováno v:
Workshop iMIMIC at MICCAI
Workshop iMIMIC at MICCAI, 2020, Lima, Peru. pp.43-53
Interpretable and Annotation-Efficient Learning for Medical Image Computing ISBN: 9783030611651
iMIMIC/MIL3iD/LABELS@MICCAI
Workshop iMIMIC at MICCAI, 2020, Lima, Peru. pp.43-53
Interpretable and Annotation-Efficient Learning for Medical Image Computing ISBN: 9783030611651
iMIMIC/MIL3iD/LABELS@MICCAI
Deep learning methods are widely used for medical applications to assist medical doctors in their daily routines. While performances reach expert's level, interpretability (highlight how and what a trained model learned and why it makes a specific de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::72b786b60012e4f6e830b1369e6f0183
https://hal.archives-ouvertes.fr/hal-02916164
https://hal.archives-ouvertes.fr/hal-02916164