Detection and characterization of pancreatic lesion with artificial intelligence: The SFR 2023 artificial intelligence data challenge.

Date publication

juillet 2024

Journal

Diagnostic and interventional imaging

Auteurs

Membres identifiés du Cancéropôle Est :
Pr HOEFFEL Christine

Tous les auteurs :
Aouad T, Laurent V, Levant P, Rode A, Brillat-Savarin N, Gaillot P, Hoeffel C, Frampas E, Barat M, Russo R, Wagner M, Zappa M, Ernst O, Delagnes A, Fillias Q, Dawi L, Savoye-Collet C, Copin P, Calame P, Reizine E, Luciani A, Bellin MF, Talbot H, Lassau N

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/39048455

Résumé

The purpose of the 2023 SFR data challenge was to invite researchers to develop artificial intelligence (AI) models to identify the presence of a pancreatic mass and distinguish between benign and malignant pancreatic masses on abdominal computed tomography (CT) examinations.

Mots clés

Artificial intelligence, Computed tomography, Deep learning, Early detection of cancer, Pancreatic cancer

Référence

Diagn Interv Imaging. 2024 07 23;: