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王绥学 的个人主页
  • 王绥学
  1. 职  务:教师
  2. 学  院:版权所有:bevictor伟德官网·(中国)唯一官方网站
  3. 学历职称:博士/副研究员
  4. 导师类型:硕士生导师
  5. 联系方式:wangsuixue@hainanu.edu.cn
个人简介 发表论文 专利情况

[1] Wang S, Zhang S, Lai H, et al. POMP: Pathology-omics multimodal pre-training framework for cancer survival prediction[C]//Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence (IJCAI), 2025, 7813-7821.


[2] Wang S, Huo W, Zhang S, et al. Higher-order logical knowledge representation learning[C]//Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence (IJCAI), 2025, 3398-3406.


[3] Wang S, Zhang S, Zhang Q, et al. MASTER: A multi-granularity invariant structure clustering scheme for multi-view clustering[C]//Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence (IJCAI), 2025, 6415-6423.


[4] Wang S, Zheng Z, Wang X, et al. A cloud-edge collaboration framework for cancer survival prediction to develop medical consumer electronic devices[J]. IEEE Transactions on Consumer Electronics, 2024, 70(3): 5251-5258.


[5] Wang S, Lai H, Wang S, et al. ContraMAE: Contrastive alignment masked autoencoder framework for cancer survival prediction[C]//2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024, 2621-2626.


[6] Wang S, Hu X, Zhang Q. HC-MAE: Hierarchical cross-attention masked autoencoder integrating histopathological images and multi-omics for cancer survival prediction[C]//2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023, 642-647.


[7] Wang S, Wang S, Liu Z, et al. A role distinguishing Bert model for medical dialogue system in sustainable smart city[J]. Sustainable Energy Technologies and Assessments, 2023, 55: 102896.


[8] Zhang S, Wang S, Zhang Q, et al. SAMGTD: Spatial-aware masked graph Transformer-diffusion model for enhanced cell type deconvolution in spatial transcriptomics[C]//Proceedings of the AAAI Conference on Artificial Intelligence, 2026, 40(21): 18020-18027.


[9] Huo W, Zhang S, Wang S, et al. SSL-CST: Cell segmentation for single-cell spatial transcriptome based on self-supervised learning[C]//Proceedings of the AAAI Conference on Artificial Intelligence, 2026, 40(21): 17499-17507.



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