摘要
中文医疗命名实体识别是人工智能和医疗领域深度融合形成的跨学科应用技术,其目的是从中文医疗记录中识别并归类与医疗相关的实体名称至预定义类别,是对医疗记录进行数据挖掘与信息抽取的前提。本文对中文医疗命名实体识别技术进行了介绍,梳理了基于深度学习方法的相关模型及其创新点,总结了该领域常用的数据集和评估指标,最后针对其未来研究方向提出了一些观点,为后续的研究提供了参考思路。
Chinese medical named entity recognition is an interdisciplinary application technology formed by the in-depth integration of artificial intelligence and the medical field.Its purpose is to identify and classify medical-related entity names from Chinese medical records into predefined categories,and it serves as a prerequisite for conducting data mining and information extraction on medical records.This paper introduces Chinese medical named entity recognition technology,sorts out the relevant models based on deep learning methods and their innovations,summarizes the commonly used datasets and evaluation metrics in this field,and finally puts forward several viewpoints on its future research directions,so as to provide reference ideas for subsequent related research.
出处
《科技风》
2026年第2期58-60,共3页
基金
四川旅游学院校级科研项目(2022SCTU ZK98)。
关键词
中文医疗命名实体识别
人工智能
深度学习
Chinese medical named entity recognition
artificial intelligence
deep learning
