| FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents G Jaume, HK Ekenel, JP Thiran International Conference on Document Analysis and Recognition (ICDAR), 2019 | 411 | 2019 |
| Towards a general-purpose foundation model for computational pathology RJ Chen, T Ding, MY Lu, DFK Williamson, G Jaume, AH Song, B Chen, ... Nature Medicine, 2024 | 321* | 2024 |
| A visual-language foundation model for computational pathology MY Lu, B Chen, DFK Williamson, RJ Chen, I Liang, T Ding, G Jaume, ... Nature Medicine, 2024 | 213* | 2024 |
| Hierarchical Graph Representations in Digital Pathology P Pati*, G Jaume*, A Foncubierta, F Feroce, AM Anniciello, ... Medical Image Analysis (MedIA), 2021 | 131 | 2021 |
| Artificial intelligence for digital and computational pathology AH Song*, G Jaume*, DFK Williamson, MY Lu, A Vaidya, TR Miller, ... Nature Reviews Bioengineering, 2023 | 128 | 2023 |
| Bracs: A dataset for breast carcinoma subtyping in h&e histology images N Brancati, AM Anniciello, P Pati, D Riccio, G Scognamiglio, G Jaume, ... Database 2022, 2022 | 102 | 2022 |
| Quantifying explainers of graph neural networks in computational pathology G Jaume*, P Pati*, B Bozorgtabar, A Foncubierta, AM Anniciello, F Feroce, ... IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 | 101 | 2021 |
| Hact-net: A hierarchical cell-to-tissue graph neural network for histopathological image classification P Pati*, G Jaume*, LA Fernandes, A Foncubierta-Rodríguez, F Feroce, ... International Conference on Medical Image Computing and Computer-Assisted …, 2020 | 87 | 2020 |
| HistoCartography: A Toolkit for Graph Analytics in Digital Pathology G Jaume*, P Pati*, V Anklin, A Foncubierta, M Gabrani International Conference on Medical Image Computing and Computer-Assisted …, 2021 | 54 | 2021 |
| Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs V Anklin*, P Pati*, G Jaume*, B Bozorgtabar, A Foncubierta-Rodríguez, ... International Conference on Medical Image Computing and Computer-Assisted …, 2021 | 52 | 2021 |
| Towards explainable graph representations in digital pathology G Jaume*, P Pati*, A Foncubierta-Rodriguez, F Feroce, G Scognamiglio, ... ICML workshop on Computational Biology, 2020 | 48 | 2020 |
| Differentiable Zooming for Multiple Instance Learning on Whole-Slide Images K Thandiackal, B Chen, P Pati, G Jaume, DFK Williamson, M Gabrani, ... European Conference on Computer Vision (ECCV), 2022 | 43 | 2022 |
| Modeling Dense Multimodal Interactions Between Biological Pathways and Histology for Survival Prediction G Jaume, A Vaidya, R Chen, D Williamson, P Liang, F Mahmood IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 | 38 | 2023 |
| Analysis of 3D pathology samples using weakly supervised AI AH Song, M Williams, DFK Williamson, SSL Chow, G Jaume, G Gao, ... Cell, 2024 | 24* | 2024 |
| Demographic bias in misdiagnosis by computational pathology models A Vaidya, RJ Chen, DFK Williamson, AH Song, G Jaume, Y Yang, ... Nature Medicine, 2024 | 23 | 2024 |
| Weakly Supervised Joint Whole-Slide Segmentation and Classification in Prostate Cancer P Pati*, G Jaume*, Z Ayadi, K Thandiackal, B Bozorgtabar, M Gabrani, ... Medical Image Analysis (MedIA), 2023 | 23 | 2023 |
| Extracting structured information from a document containing filled form images AF Rodriguez, G Jaume, M Gabrani US Patent 10,755,039, 2020 | 20 | 2020 |
| Morphological Prototyping for Unsupervised Slide Representation Learning in Computational Pathology AH Song, RJ Chen, T Ding, DFK Williamson, G Jaume, F Mahmood IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024 | 18 | 2024 |
| Transcriptomics-guided Slide Representation Learning in Computational Pathology G Jaume, L Oldenburg, A Vaidya, RJ Chen, DFK Williamson, T Peeters, ... IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024 | 16 | 2024 |
| edGNN: a Simple and Powerful GNN for Directed Labeled Graphs G Jaume*, A Nguyen*, MR Martínez, JP Thiran, M Gabrani ICLR workshop on Relational Representation Learning, 2019 | 14 | 2019 |
Faisal MahmoodAssociate Professor, Harvard UniversityVerified email at fas.harvard.edu
