Can AI predict epithelial lesion categories via automated analysis of cervical biopsies: The TissueNet challenge?

Autor: Nicolas Loménie, Capucine Bertrand, Rutger H.J. Fick, Saima Ben Hadj, Brice Tayart, Cyprien Tilmant, Isabelle Farré, Soufiane Z. Azdad, Samy Dahmani, Gilles Dequen, Ming Feng, Kele Xu, Zimu Li, Sophie Prevot, Christine Bergeron, Guillaume Bataillon, Mojgan Devouassoux-Shisheboran, Claire Glaser, Agathe Delaune, Séverine Valmary-Degano, Philippe Bertheau

Publikováno v: Journal of Pathology Informatics, Vol 13, Iss , Pp 100149- (2022)

The French Society of Pathology (SFP) organized its first data challenge in 2020 with the help of the Health Data Hub (HDH). The organization of this event first consisted of recruiting nearly 5000 cervical biopsy slides obtained from 20 pathology ce

Externí odkaz: https://doaj.org/article/9fabf64a27e84c37b5ea8552ffde4110

A Partial Label-Based Machine Learning Approach For Cervical Whole-Slide Image Classification: The Winning TissueNet Solution

Autor: Rutger H J, Fick, Brice, Tayart, Capucine, Bertrand, Solene Chan, Lang, Tina, Rey, Francesco, Ciompi, Cyprien, Tilmant, Isabelle, Farre, Saima Ben, Hadj

Publikováno v: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

Cervical cancer is the fourth most common cancer in women worldwide. To determine early treatment for patients, it is critical to accurately classify the cervical intraepithelial lesion status based on a microscopic biopsy. Lesion classification is a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::76223253cafec522da412bb55764de88
https://doi.org/10.1109/embc46164.2021.9631009

ERRα promotes breast cancer cell dissemination to bone by increasing RANK expression in primary breast tumors

Autor: Jane E. Aubin, Geoffrey Vargas, Edith Bonnelye, Sophie Vacher, Marie Brevet, Pascal Reboul, M Filipits, Ivan Bièche, C Boyault, W Jacot, Lamia Bouazza, Sandra Geraci, Keltouma Driouch, Francesco Pantano, Michael Gnant, Catherine Alix-Panabières, M Gervais, Laure Cayrefourcq, Philippe Clézardin, M Bouchet, M Mazel, Martine Croset, Claire Benetollo, C Kan, Martine Duterque-Coquillaud

Publikováno v: Oncogene
Oncogene, Nature Publishing Group, 2019, 38 (7), pp.950-964. ⟨10.1038/s41388-018-0579-3 ⟩
Oncogene, Nature Publishing Group, 2019, 38 (7), pp.950-964. ⟨10.1038/s41388-018-0579-3⟩
Oncogene, 2019, 38 (7), pp.950-964. ⟨10.1038/s41388-018-0579-3⟩

International audience; Bone is the most common metastatic site for breast cancer. Estrogen-related-receptor alpha (ERRα) has been implicated in cancer cell invasiveness. Here, we established that ERRα promotes spontaneous metastatic dissemination

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::673afe46894df907867170c048c800d7
http://hdl.handle.net/20.500.12210/55264