健康自然语言处理：方法学发展与应用
Health Natural Language Processing: Methodology Development and Applications.
作者信息
Hao Tianyong, Huang Zhengxing, Liang Likeng, Weng Heng, Tang Buzhou
机构信息
School of Computer Science, South China Normal University, Guangzhou, China.
College of Computer Science and Technology, Zhejiang University, Guangzhou, China.
出版信息
JMIR Med Inform. 2021 Oct 21;9(10):e23898. doi: 10.2196/23898.
Abstract
With the rapid growth of information technology, the necessity for processing substantial amounts of health data using advanced information technologies is increasing. A large amount of valuable data exists in natural text such as diagnosis text, discharge summaries, online health discussions, and eligibility criteria of clinical trials. Health natural language processing, as an interdisciplinary field of natural language processing and health care, plays a substantial role in a wide scope of both methodology development and applications. This editorial shares the most recent methodology innovations of health natural language processing and applications in the medical domain published in this JMIR Medical Informatics special theme issue entitled "Health Natural Language Processing: Methodology Development and Applications".
摘要
随着信息技术的迅速发展，使用先进信息技术处理大量健康数据的必要性日益增加。自然文本中存在大量有价值的数据，如诊断文本、出院小结、在线健康讨论以及临床试验的入选标准。健康自然语言处理作为自然语言处理和医疗保健的交叉领域，在方法开发和应用的广泛范围内发挥着重要作用。本社论分享了发表在《医学互联网研究杂志：医学信息学》“健康自然语言处理：方法开发与应用”这一专题特刊上的健康自然语言处理的最新方法创新及其在医学领域的应用。
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