PRISM: Mitigating EHR Data Sparsity via Learning from Missing Feature Calibrated Prototype Patient Representations.

@inproceedings{zhu-2024-prism, author = {Yinghao Zhu and Zixiang Wang and Long He and Shiyun Xie and Xiaochen Zheng and Liantao Ma and Chengwei Pan}, editor = {Edoardo Serra and Francesca Spezzano}, title = {{PRISM: Mitigating EHR Data Sparsity via Learning from Missing Feature Calibrated Prototype Patient Representations}}, booktitle = {{Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024}}, pages = {3560--3569}, publisher = {ACM}, year = {2024}, url = {https://doi.org/10.1145/3627673.3679521}, doi = {https://doi.org/10.1145/3627673.3679521} }