| Year | Type | Title | Authors | Venue / Status |
|---|---|---|---|---|
| 2026 | Editorial | Foundation models in pathology and the challenge of clinical time | Guillaume Jaume | Annals of Oncology |
| 2026 | Preprint | Towards Spatial Transcriptomics-driven Pathology Foundation Models | Konstantin Hemker; Andrew H. Song; Cristina Almagro-Pérez; Guillaume Jaume; Sophia J. Wagner; Anurag Vaidya, et al. | Preprint |
| 2025 | Conference (Oral) | BKVision: Automated Detection and Morphological Analysis of BK Virus in Renal Transplant Biopsies | Sharifa Sahai; Ana D. Ramos-Guerra; Cristina Almagro-Pérez; Guillaume Jaume; Andrew Zhang; Helmut Rennke, et al. | MICCAI |
| 2025 | Preprint | Evidence-based diagnostic reasoning with multi-agent copilot for human pathology | Luca L. Weishaupt; Chengkuan Chen; Drew F. K. Williamson; Richard J. Chen; Guillaume Jaume; Tong Ding, et al. | Preprint |
| 2025 | In Review | A Foundation Model for Spatial Proteomics | Muhammad Shaban; Yuzhou Chang; Huaying Qiu; Yao Yu Yeo; Andrew H. Song; Guillaume Jaume, et al. | In Review |
| 2025 | Journal | Multimodal Whole Slide Foundation Model for Pathology | Tong Ding; Sophia J. Wagner; Andrew H. Song; Richard J. Chen; Ming Y. Lu; Andrew Zhang, et al. | Nature Medicine |
| 2025 | Journal | Molecular-driven Foundation Model for Oncologic Pathology | Anurag Vaidya*; Andrew Zhang*; Guillaume Jaume*; Andrew H. Song; Tong Ding; Sophia J. Wagner, et al. | In Press |
| 2024 | Conference (Spotlight) | HEST-1k: A Dataset Integrating Spatial Transcriptomics and Histology Image Analysis | Guillaume Jaume; Paul Doucet; Andrew H. Song; Ming Y. Lu; Cristina Almagro-Pérez; Sophia J. Wagner, et al. | NeurIPS |
| 2024 | Conference (Oral) | Transcriptomics-guided Slide Representation Learning in Computational Pathology | Guillaume Jaume; Lukas Oldenburg; Anurag Vaidya; Richard J. Chen; Drew F. K. Williamson; Thomas Peeters, et al. | CVPR |
| 2024 | Conference | Modeling Dense Multimodal Interactions Between Biological Pathways and Histology for Survival Prediction | Guillaume Jaume; Anurag Vaidya; Richard J. Chen; Drew F. K. Williamson; Paul Pu Liang; Faisal Mahmood, et al. | CVPR |
| 2024 | Conference | Multimodal Prototyping for cancer survival prediction | Andrew H. Song; Richard J. Chen; Guillaume Jaume; Anurag Jayant Vaidya; Alexander Baras; Faisal Mahmood, et al. | ICML |
| 2024 | Conference (Oral) | Morphological Prototyping for Unsupervised Slide Representation Learning in Computational Pathology | Andrew H. Song; Richard J. Chen; Tong Ding; Drew F. K. Williamson; Guillaume Jaume; Faisal Mahmood, et al. | CVPR |
| 2024 | Conference | Multistain Pretraining for Slide Representation Learning in Pathology | Guillaume Jaume; Anurag Vaidya; Andrew Zhang; Andrew H. Song; Richard J. Chen; Sharifa Sahai, et al. | ECCV |
| 2024 | Journal | Analysis of 3D pathology samples using weakly supervised AI | Andrew H. Song; Mane Williams; Drew F. K. Williamson; Sarah S.L. Chow; Guillaume Jaume; Gan Gao, et al. | Cell |
| 2024 | Journal | Examining Demographic Bias in Misdiagnosis by AI-Driven Computational Pathology Models | Anurag Vaidya; Richard J. Chen; Drew F. K. Williamson; Andrew H. Song; Guillaume Jaume; Yuzhe Yang, et al. | Nature Medicine |
| 2024 | Journal | A Visual-Language Foundation Model for Computational Pathology | Ming Y. Lu; Drew F. K. Williamson; Andrew H. Song; Richard J. Chen; Guillaume Jaume; Anurag Vaidya, et al. | Nature Medicine |
| 2024 | Journal | Towards a General-Purpose Foundation Model for Computational Pathology | Richard J. Chen; Tong Ding; Ming Y. Lu; Drew F. K. Williamson; Guillaume Jaume; Andrew H. Song, et al. | Nature Medicine |
| 2024 | In Review | Deep Learning-based Modeling for Preclinical Drug Safety Assessment | Guillaume Jaume; Simone de Brot; Andrew H. Song; Drew F. K. Williamson; Lukas Oldenburg; Andrew Zhang, et al. | In Review |
| 2024 | In Review | AI-driven Discovery of Morphomolecular Signatures in Toxicology | Guillaume Jaume; Thomas Peeters; Andrew H. Song; Rowland Pettit; Drew F. K. Williamson; Lukas Oldenburg, et al. | In Review |
| 2023 | Review | Artificial Intelligence for Digital and Computational Pathology | Andrew H. Song; Guillaume Jaume; Drew F. K. Williamson; Ming Y. Lu; Anurag Vaidya; Tiffany R. Miller, et al. | Nature Reviews Bioengineering |
| 2023 | Journal | Weakly Supervised Learning for Joint Whole-Slide Segmentation and Classification in Prostate Cancer | Pushpak Pati; Guillaume Jaume; Zeineb Ayadi; Kevin Thandiackal; Behzad Bozorgtabar; Maria Gabrani, et al. | Medical Image Analysis |
| 2022 | Conference | Differentiable Zooming for Multiple Instance Learning on Whole-Slide Images | Kevin Thandiackal; Boqi Chen; Pushpak Pati; Guillaume Jaume; Drew F. K. Williamson; Maria Gabrani, et al. | ECCV |
| 2021 | Journal | Hierarchical Graph Representations in Digital Pathology | Guillaume Jaume; Pushpak Pati; Antonio Foncubierta-Rodríguez; Florinda Feroce; Anna Maria Anniciello; Tilman Rau, et al. | Medical Image Analysis |
| 2021 | Conference | Quantifying Explainers of Graph Neural Networks in Computational Pathology | Guillaume Jaume; Pushpak Pati; Behzad Bozorgtabar; Antonio Foncubierta-Rodríguez; Florinda Feroce; Anna Maria Anniciello, et al. | CVPR |
Jaume Lab
AI for Oncologic Pathology. Agentic, multimodal and foundational.