Papers by Lequan Yu
CTPD: Cross-Modal Temporal Pattern Discovery for Enhanced Multimodal Electronic Health Records Analysis (2025.findings-acl)
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| Challenge: | Existing methods for predicting clinical outcomes have focused on capturing temporal interactions within individual samples and fusing multimodal information, overlooking critical temporal patterns across different patients. |
| Approach: | They propose a cross-modal temporal pattern discovery framework to extract temporal patterns from multimodal EHR data. |
| Outcome: | The proposed framework extracts meaningful cross-modal temporal patterns from multimodal EHR data. |
Relabeling Minimal Training Subset to Flip a Prediction (2024.findings-eacl)
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| Challenge: | Existing methods to identify and relabel training subsets that can flip a prediction are not efficient, argues a new study. |
| Approach: | They propose an algorithm to identify and relabel the smallest training subset St needed to flip a prediction. |
| Outcome: | The proposed algorithm can flip a prediction on a test point xt with 2% of training points . the proposed method can be used for multiple purposes including evaluating model robustness . |