Papers by Shang-Chi Tsai
Modeling Diagnostic Label Correlation for Automatic ICD Coding (2021.naacl-main)
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| Challenge: | Existing work built a binary prediction for each label independently, ignoring the dependencies between labels. |
| Approach: | They propose a framework to capture the label correlation and train a reranking estimator to rescore the probability of each label set candidate generated by a base predictor. |
| Outcome: | The proposed framework improves on the best-performing predictors on MIMIC datasets. |
Leveraging Hierarchical Category Knowledge for Data-Imbalanced Multi-Label Diagnostic Text Understanding (D19-62)
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| Challenge: | Existing work on automatic diagnosis prediction has considered the output labels independently, so that the codes with few samples are difficult to learn. |
| Approach: | They propose to leverage domain knowledge to predict diagnostic codes given the descriptive present illness in electronic health records by leveraging hierarchical category knowledge. |
| Outcome: | The proposed model can efficiently utilize category knowledge and provide informative cues to improve the top-ranked diagnostic codes which is better than the prior state-of-the-art. |