Paverd H, Gao Z, Mahani G, Fabre MA, Burge S, Hoare M, Crispin-Ortuzar M. LLM-based reconstruction of longitudinal clinical trajectories in chronic liver disease. npj Precision Oncology, 2026. https://doi.org/10.1038/s41698-026-01650-4.
Wu L, Liu J, Zhang D, Gong Z, Zhan Y, Niu Y, Ge J, Yang C, Yi K, Crispin-Ortuzar M, Li C, Gao Z. Modeling Whole-Slide Images as Dynamic Tumor Microenvironment Fields. Accepted to Advances in Neural Information Processing Systems (NeurIPS), 2026.
Gao Z, He K, Su W, Pang X, Machado I P, Jimenez-Linan M, Rous B, Wang C, Li C, McGough W, Gao S, Zhang D, Gong T, Lu M Y, Mahmood F, Feng M, Li C, Crispin-Ortuzar M. ALPaCA: Adapting Llama for Pathology Context Analysis to enable slide-level question answering[J]. Nature Communications, 2026. https://doi.org/10.1038/s41467-026-76372-z.
D Zhang, J Liu, Y Ma, J Ge, Z Zeng, W Sun, Q Liu, K He, Y Zheng, W Yu, C Li*, Z Gao*. Learnable frozen feature augmentation for few-shot biomarker prediction from pathology whole-slide images. Bioinformatics, 2026, btag597.
Gao Z, Ge J, Lu J, Wu L, Clayton H, Zhang D, Liu J, Machado I P, Chen Y, Crispin-Ortuzar M, Li C. From cells to patients: Multiscale computational pathology in the era of foundation models and vision-language systems[J]. Intelligent Oncology, 2026, 2(3): 100074.
Niu J, Chen J, Zhang D, Lu J, Liao Z, Liu X, Zhong H, Crispin-Ortuzar M, Li C, Gao Z*, Cai Y*. AGE-MIL: Anchor-Guided Evidence Learning for Patient-Level Prediction. Accepted to the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2026.
Yang C, Liu Q, Zhao W, Tang Y, Ge J, Zhang D, Liu J, Wu L, Lu J, Zhang N, Wu X, Gao Z, Li C. PathNavigate: A Training-Free Pathology Agent with Surprise-Guided Scan and Shared Slide Memory for Whole-Slide Image VQA. Accepted to Advances in Neural Information Processing Systems (NeurIPS), 2026.
Ge J, Zhan Y, Zhao W, Zhang D, Wang K, Liu J, Yang C, Li C, Zhang J, Dong Y, Zhang N, Liu Q, Crispin-Ortuzar M, Fu H, Li C, Gao Z. Thinking in Scales: Accelerating Gigapixel Pathology Image Analysis via Adaptive Continuous Reasoning. Accepted to the International Conference on Machine Learning (ICML), 2026.
D Zhang, Z Gong, X Pang, J Liu, J Lu, H Cui, J Ge, Z Zeng, K Yi, Y Li, S Liu, T Yu, H Wang, M Crispin-Ortuzar, W Yu, C Li, Z Gao*. CARE: A Molecular-Guided Foundation Model with Adaptive Region Modeling for Whole Slide Image Analysis. Accepted to IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.
Niu Y, Liu J, Zhan Y, Shi J, Zhang D, Reinius M, Machado I, Crispin-Ortuzar M, Wu J, Li C, Gao Z*. PH2ST: Prompt-Guided Hypergraph Learning for Spatial Transcriptomics Prediction in Whole Slide Images[J]. Medical Image Analysis, 2026: 104008.
Yang C, Zhao W, Tang Y, Lu J, Ge J, Liu Q, Gao Z*, Li C. HAAF: Hierarchical Adaptation and Alignment of Foundation Models for Few-Shot Pathology Anomaly Detection. Accepted to The Web Conference (WWW), 2026.
Kaura SK, Wu J, Gao Z*, Li C*. MegaSeg: Towards Scalable Semantic Segmentation for Megapixel Images. Medical Image Analysis. 2026 Jan 10:103933.
Niu Y, Liu J, Zhan Y, Shi J, Chen J, Zhang D, Li C, Gao Z*. Learning Heterogeneous Embedding with Prototype-Aware Graph Attention for Whole Slide Image Classification[C]. 2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025: 2671-2678.
Gao Z., Mao, A., Dong, Y. et al. SMMILe enables accurate spatial quantification in digital pathology using multiple-instance learning. Nat Cancer (2025).
Ge J, Zhang D, Zhan Y, Liu J, Gong T, Wu J, Crispin M, Li C, Gao Z*. ProGIS: Prototype-Guided Interactive Segmentation for Pathological Images. IEEE Transactions on Medical Imaging. 2025.
Zhang D, Ge J, Liu J, Wang C, Gong T, Gao Z*, Li C*. StaDis: Stability distance to detecting out-of-distribution data in computational pathology. Medical Image Analysis. 2025 Aug 27:103774.
Wang, C., Ge, J., Niu, Y., Ding, C., Fan, Y., Chang, H., Yang, Z., Ran, C., Teng, X., Wang, X., Wu, L., Gao, Z.*, Li, C.* (2025). A fully annotated pathology slide dataset for early gastric cancer and precancerous lesions. Scientific Data, 12.
W Knottenbelt, W McGough, R Wray, W Zhang, J Liu, I Machado, Z Gao*, M Crispin*, CoxKAN: Kolmogorov-Arnold networks for interpretable, High-Performance survival analysis, Bioinformatics, 2025
Zhang Y1, Gao Z1, He K, et al. From patches to WSIs: A systematic review of deep Multiple Instance Learning in computational pathology[J]. Information Fusion, 2025: 103027.
X Wang, W Su, Y Dong, Y Li, X Zhang, T Gong, IP Machado, M Crispin-Ortuzar, C Li, Z Gao*. Shallow-Deep Synergy: Boosting Cross-Domain Generalization in Histopathological Image Segmentation[C]//2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2024: 3790-3794.
J Liu, A Mao, Y Niu, X Zhang, T Gong, C Li, Z Gao*. Pamil: Prototype attention-based multiple instance learning for whole slide image classification[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Cham: Springer Nature Switzerland, 2024: 362-372.
Wang C, Wang X, Gao Z, Ran C, Li C, Ding C. Multiple serous cavity effusion screening based on smear images using vision transformer[J]. Scientific Reports, 2024, 14(1): 7395.
Shi J, Tang L, Gao Z, Li Y, Wang C, Gong T, Li C, Fu H. MG-trans: Multi-scale graph transformer with information bottleneck for whole slide image classification[J]. IEEE Transactions on Medical Imaging, 2023, 42(12): 3871-3883.
Shi J, Tang L, Li Y, Zhang X, Gao Z, Zheng Y, Wang C, Gong T, Li C. A structure-aware hierarchical graph-based multiple instance learning framework for pt staging in histopathological image[J]. IEEE Transactions on Medical Imaging, 2023, 42(10): 3000-3011.
Gao Z, Mao A, Wu K, et al. Childhood leukemia classification via information bottleneck enhanced hierarchical multi-instance learning[J]. IEEE Transactions on Medical Imaging, 2023, 42(8): 2348-2359.
Gao Z, Hong B, Li Y, et al. A semi-supervised multi-task learning framework for cancer classification with weak annotation in whole-slide images[J]. Medical Image Analysis, 2023, 83: 102652.
Gao Z, Mao A, Wu J, et al. Uncertainty-based Model Acceleration for Cancer Classification in Whole-Slide Images[C]//2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2022: 1534-1538.
Gao Z, Jia C, Li Y, et al. Unsupervised representation learning for tissue segmentation in histopathological images: From global to local contrast[J]. IEEE Transactions on Medical Imaging, 2022, 41(12): 3611-3623.
Gao Z, Hong B, Zhang X, et al. Instance-based vision transformer for subtyping of papillary renal cell carcinoma in histopathological image[C]//International conference on medical image computing and computer-assisted intervention. Cham: Springer International Publishing, 2021: 299-308.
Gao Z, Shi J, Zhang X, et al. Nuclei grading of clear cell renal cell carcinoma in histopathological image by composite high-resolution network[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Cham: Springer International Publishing, 2021: 132-142.
Gao Z, Puttapirat P, Shi J, et al. Renal cell carcinoma detection and subtyping with minimal point-based annotation in whole-slide images[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Cham: Springer International Publishing, 2020: 439-448.
Invited talk at Department of Genomic Medicine Summer Conference 2026, Cambridge, UK
Invited talk at AI in Oncology 2026, Paris, France
Invited talk at Artificial Intelligence for Oncology Conference 2026, Milan, Italy
Invited webinar talk at 5th Webinar on Artificial Intelligence in Precision Oncology, Online
Poster presentation at ESMO AI & Digital Oncology Congress 2025, Berlin, Germany
Invited talk at Maison de la Chimie, 28 Rue Saint-Dominique, Paris, France
Invited lecture at Uni of Oxford's Mathematical Institute, Oxford, UK
Invited lecture at Ionian Academy /Ionian University 1, Kapodistriou str., Corfu, Greece
Poster presentation at Artificial Intelligence for Oncology Conference 2025, Milan, Italy
Poster presentation at AACR Annual Meeting 2025, Chicago, US
Flash talk and poster at CRUK CI/CC Retreat 2024, Cambridge, UK
Invited talk at ICM Symposium 2024, Cambridge, UK
Invited talk at C2D3 Computational Biology Annual Symposium 2024, Cambridge, UK