Yang, Sen

Transformer-based unsupervised contrastive learning for histopathological image classification

Wang, X., Yang, S., Zhang, J., Wang, M., Zhang, J., Yang, W., Huang, J., & Han, X. (2022) · Medical Image Analysis

AI in cancer detectionDomain Adaptation and Few-Shot Learning

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A pathology foundation model for cancer diagnosis and prognosis prediction

Wang, X., Zhao, J., Marostica, E., Yuan, W., Jin, J., Zhang, J., Li, R., Tang, H., Wang, K., Li, Y., et al. (2024) · Nature

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

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A Vision-Language Foundation Model for Precision Oncology

Xiang, J., Wang, X., Zhang, X., Xi, Y., Eweje, F., Chen, Y., Li, Y., Bergstrom, C., Gopaulchan, M., Kim, T., et al. (2025) · Nature

AI in cancer detectionMultimodal Machine Learning Applications

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RetCCL: Clustering-guided contrastive learning for whole-slide image retrieval

Wang, X., Du, Y., Yang, S., Zhang, J., Wang, M., Zhang, J., Yang, W., Huang, J., & Han, X. (2023) · Medical Image Analysis

AI in cancer detectionImage Retrieval and Classification Techniques

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TransPath: Transformer-Based Self-supervised Learning for Histopathological Image Classification

Wang, X., Yang, S., Zhang, J., Wang, M., Zhang, J., Huang, J., Yang, W., & Han, X. (2021) · Lecture Notes in Computer Science

AI in cancer detectionDomain Adaptation and Few-Shot Learning

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PAIP 2019: Liver cancer segmentation challenge

Kim, Y. J., Jang, H., Lee, K., Park, S., Min, S.-G., Hong, C., Park, J. H., Lee, K., Kim, J., Hong, W., et al. (2021) · Medical Image Analysis

AI in cancer detectionMedical Image Segmentation Techniques

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Sch-net: a deep learning architecture for automatic detection of schizophrenia

Fu, J., Yang, S., He, F., He, L., Li, Y., Zhang, J., & Xiong, X. (2021) · BioMedical Engineering OnLine

Speech Recognition and SynthesisSchizophrenia research and treatment

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