Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients N Lassau, S Ammari, E Chouzenoux, H Gortais, P Herent, M Devilder, ... Nature communications 12 (1), 1-11, 2021 | 177 | 2021 |
Learning spatiotemporal trajectories from manifold-valued longitudinal data JB Schiratti, S Allassonniere, O Colliot, S Durrleman Advances in neural information processing systems 28, 2015 | 99 | 2015 |
A Bayesian mixed-effects model to learn trajectories of changes from repeated manifold-valued observations JB Schiratti, S Allassonnière, O Colliot, S Durrleman Journal of Machine Learning Research 18 (133), 1-33, 2017 | 81 | 2017 |
Using stylegan for visual interpretability of deep learning models on medical images K Schutte, O Moindrot, P Hérent, JB Schiratti, S Jégou arXiv preprint arXiv:2101.07563, 2021 | 61 | 2021 |
An ensemble learning approach to detect epileptic seizures from long intracranial EEG recordings JB Schiratti, JE Le Douget, M Le Van Quyen, S Essid, A Gramfort 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 50 | 2018 |
A deep learning method for predicting knee osteoarthritis radiographic progression from MRI JB Schiratti, R Dubois, P Herent, D Cahané, J Dachary, T Clozel, ... Arthritis Research & Therapy 23, 1-10, 2021 | 47 | 2021 |
Abdominal musculature segmentation and surface prediction from CT using deep learning for sarcopenia assessment P Blanc-Durand, JB Schiratti, K Schutte, P Jehanno, P Herent, F Pigneur, ... Diagnostic and Interventional Imaging 101 (12), 789-794, 2020 | 43 | 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 | 36 | 2023 |
Spatiotemporal propagation of the cortical atrophy: Population and individual patterns I Koval, JB Schiratti, A Routier, M Bacci, O Colliot, S Allassonnière, ... Frontiers in neurology 9, 235, 2018 | 36 | 2018 |
Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks I Koval, JB Schiratti, A Routier, M Bacci, O Colliot, S Allassonnière, ... Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 33 | 2017 |
A mixed-effects model with time reparametrization for longitudinal univariate manifold-valued data JB Schiratti, S Allassonniere, A Routier, ... Information Processing in Medical Imaging: 24th International Conference …, 2015 | 30 | 2015 |
An artificial intelligence model predicts the survival of solid tumour patients from imaging and clinical data K Schutte, F Brulport, S Harguem-Zayani, JB Schiratti, R Ghermi, ... European Journal of Cancer 174, 90-98, 2022 | 9 | 2022 |
AI-based multi-modal integration of clinical characteristics, lab tests and chest CTs improves COVID-19 outcome prediction of hospitalized patients N Lassau, S Ammari, E Chouzenoux, H Gortais, P Herent, M Devilder, ... medRxiv, 2020.05. 14.20101972, 2020 | 9 | 2020 |
Mixed-effects model for the spatiotemporal analysis of longitudinal manifold-valued data JB Schiratti, S Allassonnière, O Colliot, S Durrleman 5th MICCAI Workshop on Mathematical Foundations of Computational Anatomy, 2015 | 8 | 2015 |
Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients. Nat Commun. 2021; 12: 634 N Lassau, S Ammari, E Chouzenoux, H Gortais, P Herent, M Devilder, ... | 8 | |
Methods and algorithms to learn spatio-temporal changes from longitudinal manifold-valued observations JB Schiratti Université Paris Saclay (COmUE), 2017 | 6 | 2017 |
Semiautomated segmentation of hepatocellular carcinoma tumors with MRI using convolutional neural networks D Said, G Carbonell, D Stocker, S Hectors, N Vietti-Violi, O Bane, X Chin, ... European Radiology 33 (9), 6020-6032, 2023 | 4 | 2023 |
Integration of clinical characteristics, lab tests and a deep learning CT scan analysis to predict severity of hospitalized COVID-19 patients N Lassau, S Ammari, E Chouzenoux, H Gortais, P Herent, M Devilder, ... MedRxiv, 2020 | 3 | 2020 |
623MO Machine Learning-based prediction of germinal center, MYC/BCL2 double protein expressor status, and MYC rearrangement from whole slide images in DLBCL patients C Syrykh, JB Schiratti, E Brion, C Joubert, M Baia, L Marlot, C Maussion, ... Annals of Oncology 33, S829, 2022 | 2 | 2022 |
Method for determining the temporal progression of a biological phenomenon and associated methods and devices S Durrleman, JB Schiratti, S Allassonniere, O Colliot US Patent 10,832,089, 2020 | 1 | 2020 |