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Leveraging Multiple Types of Domain Knowledge for Safe and Effective Drug Recommendation.

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A Statistical Study of Words Used in Chinese Clinical Documents., and . AMIA, AMIA, (2014)Cross-Modal Contrastive Learning for Event Extraction., , , , , and . DASFAA (3), volume 13945 of Lecture Notes in Computer Science, page 699-715. Springer, (2023)Automatic Knowledge Extraction and Data Mining from Echo Reports of Pediatric Heart Disease: Application on Clinical Decision Support., , , , , , and . CCL, volume 9427 of Lecture Notes in Computer Science, page 417-424. Springer, (2015)Lexical Characteristics Analysis of Chinese Clinical Documents., , and . BioNLP@IJCNLP, page 114-120. Association for Computational Linguistics, (2015)Development and evaluation of task-specific NLP framework in China., , , , , , and . MedInfo, volume 216 of Studies in Health Technology and Informatics, page 1031. IOS Press, (2015)Leveraging Multiple Types of Domain Knowledge for Safe and Effective Drug Recommendation., , , , , , , , , and . CIKM, page 2169-2178. ACM, (2022)Prompt Combines Paraphrase: Teaching Pre-trained Models to Understand Rare Biomedical Words., , , , , , , , , and . COLING, page 1422-1431. International Committee on Computational Linguistics, (2022)Neural named entity recognition and temporal relation extraction. University of Manchester, UK, (2020)British Library, EThOS.A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience., , , , , , and . Neuroinformatics, 17 (3): 391-406 (2019)A Neural Layered Model for Nested Named Entity Recognition., , and . NAACL-HLT, page 1446-1459. Association for Computational Linguistics, (2018)