Nos Publications
Nous définissons une nouvelle approche
L’Apprentissage Profond est capable d’identifier des anomalies morphologiques aujourd’hui inconnues des classifications anatomopathologiques. En le combinant à l’expertise médicale, nous proposons de nouveaux biomarqueurs tumoraux affinant le diagnostic et prédisant la réponse du patient à l’arsenal thérapeutique à la disposition des médecins.
En savoir plus:Breast-NEOprAIdict: Predicting response of breast cancer patients treated with neoadjuvant chemotherapyBreast-NEOprAIdict: Predicting response of breast cancer patients treated with neoadjuvant chemotherapy
En savoir plus:MultiVarNet: Predicting tumour mutational status at the protein levelMultiVarNet: Predicting tumour mutational status at the protein level
En savoir plus:Preliminary evaluation of deep learning for first-line diagnostic prediction of tumor mutational statusPreliminary evaluation of deep learning for first-line diagnostic prediction of tumor mutational status
En savoir plus:Inter-semantic domain adversarial in histopathological imagesInter-semantic domain adversarial in histopathological images
En savoir plus:p16/Ki67 AutoReader: Retrospective diagnostic study of performancep16/Ki67 AutoReader: Retrospective diagnostic study of performance
En savoir plus:A deep learning solution for triaging patient with cancer according to their predicted mutational status using histopathological images