March 9, 2022, 2:11 a.m. | Enwei Zhu, Qilin Sheng, Huanwan Yang, Jinpeng Li

cs.CL updates on arXiv.org arxiv.org

Medical information extraction consists of a group of natural language
processing (NLP) tasks, which collaboratively convert clinical text to
pre-defined structured formats. Current state-of-the-art (SOTA) NLP models are
highly integrated with deep learning techniques and thus require massive
annotated linguistic data. This study presents an engineering framework of
medical entity recognition, relation extraction and attribute extraction, which
are unified in annotation, modeling and evaluation. Specifically, the
annotation scheme is comprehensive, and compatible between tasks, especially
for the medical relations. The …

annotation arxiv extraction framework information medical text

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