Published in Medical Image Analysis, 2025
Recommended citation: 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.
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Published in Scientific Data, 2025
Recommended citation: 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.
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Published in Bioinfomatics, 2025
Recommended citation: 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
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Published in medRxiv(preprint), 2025
Recommended citation: Gao Z, He K, Su W, et al. ALPaCA: Adapting Llama for Pathology Context Analysis to enable slide-level question answering[J]. medRxiv, 2025: 2025.04. 22.25326190.
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Published in Information Fusion, 2025
Recommended citation: 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.
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Published in MedRxiv, 2024
Recommended citation: Gao Z, Mao A, Dong Y, et al. Accurate spatial quantification in computational pathology with multiple instance learning[J]. MedRxiv, 2024: 2024.04. 25.24306364.
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Published in IEEE Transactions on Medical Imaging, 2023
Recommended citation: 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.
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Published in Medical Image Analysis, 2023
Recommended citation: 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.
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Published in IEEE Transactions on Medical Imaging, 2022
Recommended citation: 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.
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Published in 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024
Recommended citation: 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.
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Published in International Conference on Medical Image Computing and Computer-Assisted Intervention, 2024
Recommended citation: 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.
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Published in 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022
Recommended citation: 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.
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Published in International Conference on Medical Image Computing and Computer-Assisted Intervention, 2021
Recommended citation: 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.
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Published in International Conference on Medical Image Computing and Computer-Assisted Intervention, 2021
Recommended citation: 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.
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Published in International Conference on Medical Image Computing and Computer-Assisted Intervention, 2020
Recommended citation: 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.
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