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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
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Blog Post number 4
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Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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portfolio
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publications
Renal cell carcinoma detection and subtyping with minimal point-based annotation in whole-slide images
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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Nuclei Grading of Clear Cell Renal Cell Carcinoma in Histopathological Image by Composite High-Resolution Network
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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Instance-based vision transformer for subtyping of papillary renal cell carcinoma in histopathological image
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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Unsupervised representation learning for tissue segmentation in histopathological images: From global to local contrast
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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Uncertainty-based Model Acceleration for Cancer Classification in Whole-Slide Images
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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A semi-supervised multi-task learning framework for cancer classification with weak annotation in whole-slide images
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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Childhood leukemia classification via information bottleneck enhanced hierarchical multi-instance learning
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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Accurate spatial quantification in computational pathology with multiple instance learning
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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Pamil: Prototype attention-based multiple instance learning for whole slide image classification
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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Shallow-Deep Synergy: Boosting Cross-Domain Generalization in Histopathological Image Segmentation
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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From patches to WSIs: A systematic review of deep Multiple Instance Learning in computational pathology
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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ALPaCA: Adapting Llama for Pathology Context Analysis to enable slide-level question answering
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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CoxKAN: Kolmogorov-Arnold networks for interpretable, High-Performance survival analysis
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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A fully annotated pathology slide dataset for early gastric cancer and precancerous lesions
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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StaDis: Stability distance to detecting out-of-distribution data in computational pathology
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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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
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