| A deep learning model to predict RNA-Seq expression of tumours from whole slide images B Schmauch, A Romagnoni, E Pronier, C Saillard, P Maillé, J Calderaro, ... Nature communications 11 (1), 3877, 2020 | 344 | 2020 |
| Predicting survival after hepatocellular carcinoma resection using deep learning on histological slides C Saillard, B Schmauch, O Laifa, M Moarii, S Toldo, M Zaslavskiy, ... Hepatology 72 (6), 2000-2013, 2020 | 222 | 2020 |
| Diagnosis of focal liver lesions from ultrasound using deep learning B Schmauch, P Herent, P Jehanno, O Dehaene, C Saillard, C Aubé, ... Diagnostic and interventional imaging 100 (4), 227-233, 2019 | 128 | 2019 |
| Detection and characterization of MRI breast lesions using deep learning P Herent, B Schmauch, P Jehanno, O Dehaene, C Saillard, C Balleyguier, ... Diagnostic and interventional imaging 100 (4), 219-225, 2019 | 115 | 2019 |
| Self supervised learning improves dMMR/MSI detection from histology slides across multiple cancers C Saillard, O Dehaene, T Marchand, O Moindrot, A Kamoun, B Schmauch, ... arXiv preprint arXiv:2109.05819, 2021 | 38 | 2021 |
| Federated survival analysis with discrete-time cox models M Andreux, A Manoel, R Menuet, C Saillard, C Simpson arXiv preprint arXiv:2006.08997, 2020 | 27 | 2020 |
| Scaling self-supervised learning for histopathology with masked image modeling A Filiot, R Ghermi, A Olivier, P Jacob, L Fidon, A Mac Kain, C Saillard, ... medRxiv, 2023.07. 21.23292757, 2023 | 24 | 2023 |
| Validation of MSIntuit as an AI-based pre-screening tool for MSI detection from colorectal cancer histology slides C Saillard, R Dubois, O Tchita, N Loiseau, T Garcia, A Adriansen, ... Nature Communications 14 (1), 6695, 2023 | 21* | 2023 |
| Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma C Saillard, F Delecourt, B Schmauch, O Moindrot, M Svrcek, ... Nature Communications 14 (1), 3459, 2023 | 9* | 2023 |
| 1124O Prediction of distant relapse in patients with invasive breast cancer from deep learning models applied to digital pathology slides IJ Garberis, C Saillard, D Drubay, B Schmauch, V Aubert, A Jaeger, ... Annals of Oncology 32, S921, 2021 | 7 | 2021 |
| HE2RNA: a deep learning model for transcriptomic learning from digital pathology E Pronier, B Schmauch, A Romagnoni, C Saillard, J Calderaro, M Sefta, ... Cancer Res 80, 2105-2105, 2020 | 3 | 2020 |
| Deep learning allows assessment of risk of metastatic relapse from invasive breast cancer histological slides I Garberis, V Gaury, C Saillard, D Drubay, K Elgui, B Schmauch, A Jaeger, ... bioRxiv, 2022.11. 28.518158, 2022 | 2 | 2022 |
| Identification of pancreatic adenocarcinoma molecular subtypes on histology slides using deep learning models. C Saillard, F Delecourt, B Schmauch, O Moindrot, M Svrcek, ... Journal of Clinical Oncology 39 (15_suppl), 4141-4141, 2021 | 2 | 2021 |
| Systems and methods for determining breast cancer prognosis and associated features C Saillard, B Schmauch, V Aubert, A Kamoun, M Lacroix-Triki, I Garberis, ... US Patent App. 18/127,566, 2023 | 1 | 2023 |
| 920P Blind validation of MSIntuit, an AI-based pre-screening tool for MSI detection from colorectal cancer H&E slides M Svrcek, C Saillard, R Dubois, N Loiseau, P Mespoulhe, F Brulport, ... Annals of Oncology 33, S967, 2022 | 1 | 2022 |
| 147P Blind validation of an AI-based tool for predicting distant relapse from breast cancer HES stained slides IJ Garberis, V Gaury, V Aubert, D Drubay, C Saillard, K Elgui, F Bernigole, ... Annals of Oncology 33, S607, 2022 | 1 | 2022 |
| SYSTEMS AND METHODS FOR DETERMINING BREAST CANCER PROGNOSIS AND ASSOCIATED FEATURES C Saillard, B Schmauch, V Aubert, A Kamoun, M Lacroix-triki, I Garberis, ... US Patent App. 18/186,111, 2024 | | 2024 |
| AI-based identification of FGFR3 mutation status from routine histology slides of muscle-invasive bladder cancer. C Saillard, PA Bannier, P Mann, C Maussion, C Matek, A Hartmann, ... Journal of Clinical Oncology 41 (16_suppl), e16580-e16580, 2023 | | 2023 |
| Systems and methods for image preprocessing P Courtiol, O Moindrot, C Maussion, C Saillard, B Schmauch, G Wainrib US Patent 11,562,585, 2023 | | 2023 |
| Explainable Deep Learning Predicts Molecular Subtypes and Improves Risk of Relapse Assessment from Invasive Breast Cancer Histological Slides C Saillard, I Garberis, D Drubay, V Gaury, V Aubert, B Schmauch, ... LABORATORY INVESTIGATION 102 (SUPPL 1), 187-188, 2022 | | 2022 |
