Cao Xiao


2022

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Benchmarking Automated Clinical Language Simplification: Dataset, Algorithm, and Evaluation
Junyu Luo | Junxian Lin | Chi Lin | Cao Xiao | Xinning Gui | Fenglong Ma
Proceedings of the 29th International Conference on Computational Linguistics

Patients with low health literacy usually have difficulty understanding medical jargon and the complex structure of professional medical language. Although some studies are proposed to automatically translate expert language into layperson-understandable language, only a few of them focus on both accuracy and readability aspects simultaneously in the clinical domain. Thus, simplification of the clinical language is still a challenging task, but unfortunately, it is not yet fully addressed in previous work. To benchmark this task, we construct a new dataset named MedLane to support the development and evaluation of automated clinical language simplification approaches. Besides, we propose a new model called DECLARE that follows the human annotation procedure and achieves state-of-the-art performance compared with eight strong baselines. To fairly evaluate the performance, we also propose three specific evaluation metrics. Experimental results demonstrate the utility of the annotated MedLane dataset and the effectiveness of the proposed model DECLARE.

2021

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Fusion: Towards Automated ICD Coding via Feature Compression
Junyu Luo | Cao Xiao | Lucas Glass | Jimeng Sun | Fenglong Ma
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021