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

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 centers. After ensuring that patients did not refuse...

Full description

Bibliographic Details
Main Authors:	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
Format:	Article
Language:	English
Published:	Elsevier 2022-01-01
Series:	Journal of Pathology Informatics
Subjects:	Artificial intelligence Data challenge Whole slide images Uterine cervix
Online Access:	http://www.sciencedirect.com/science/article/pii/S215335392200743X

Internet

http://www.sciencedirect.com/science/article/pii/S215335392200743X

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

Internet

Similar Items