Blind validation of MSIntuit, an AI-based pre-screening tool for MSI detection from histology slides of colorectal cancer
Charlie Saillard(Laboratoire Procédés et Ingénierie en Mécanique et Matériaux), Magali Svrcek(Azienda Unita' Sanitaria Locale Di Modena), Aurélie Kamoun(La Ligue Contre le Cancer), Lionel Guillou, Arnaud Fouillet, Meriem Sefta, Nicolas Loiseau(Centre National de la Recherche Scientifique), Oussama Tchita, Rémy Dubois, Jakob Nikolas Kather(German Cancer Research Center), Aurélie Adriansen, Thierry Garcia, Stéphane Rossat, Michaël Auffret, Séverine Carpentier, J. Reyre, Diana Enéa(Sorbonne Université)
Cited by 9
Related Papers
Durable Clinical Benefit With Nivolumab Plus Ipilimumab in DNA Mismatch Repair–Deficient/Microsatellite Instability–High Metastatic Colorectal Cancer
|Journal of Clinical Oncology|2018|2.1k
Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer
|Nature Medicine|2019|1.4k
Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study
|PLoS Medicine|2019|1k
The future landscape of large language models in medicine
|Communications Medicine|2023|937
Deep learning in cancer pathology: a new generation of clinical biomarkers
|British Journal of Cancer|2020|649