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

• Main Authors: Nicolas Loménie (Author), Capucine Bertrand (Author), Rutger H.J. Fick (Author), Saima Ben Hadj (Author), Brice Tayart (Author), Cyprien Tilmant (Author), Isabelle Farré (Author), Soufiane Z. Azdad (Author), Samy Dahmani (Author), Gilles Dequen (Author), Ming Feng (Author), Kele Xu (Author), Zimu Li (Author), Sophie Prevot (Author), Christine Bergeron (Author), Guillaume Bataillon (Author), Mojgan Devouassoux-Shisheboran (Author), Claire Glaser (Author), Agathe Delaune (Author), Séverine Valmary-Degano (Author), Philippe Bertheau (Author)
• Format: Book
• Published: Elsevier, 2022-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

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...