Chemo-prAIdict Breast: A deep learning solution for predicting residual disease on biopsies of breast cancer patients treated with neoadjuvant chemotherapy.

Fiche publication

Date publication

janvier 2026

Journal

European journal of cancer (Oxford, England : 1990)

Auteurs

Membres identifiés du Cancéropôle Est :
Dr ARNOULD Laurent , Pr COUTANT Charles , Dr LADOIRE Sylvain , Dr DESMOULINS Isabelle , Dr DERANGERE Valentin , Dr HENNEQUIN Audrey , Dr MAYEUR Didier

Tous les auteurs :
Valderrama NF, Morel LO, Mweze DT, Derangère V, Desmoulins I, Mayeur D, Kaderbhai C, Ilie S, Hennequin A, Roussot N, Bergeron A, Beltjens F, Pescia C, Morel HP, Coutant C, Rittscher J, Arnould L, Vinçon N, Ladoire S

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/41518683

Résumé

Predicting chemosensitivity before treatment could help tailor neoadjuvant chemotherapy (NAC) in early breast cancer (eBC). Pathological complete response (pCR) is associated with better long term survival, but yet no robust baseline predictor is available.