Health Natural Language Processing: Methodology Development and Applications

被引：27

作者：

Hao, Tianyong ^{[1
]}

Huang, Zhengxing ^{[2
]}

Liang, Likeng ^{[1
]}

Weng, Heng ^{[3
]}

Tang, Buzhou ^{[4
]}

机构：

[1] South China Normal Univ, Sch Comp Sci, Guangzhou, Peoples R China

[2] Zhejiang Univ, Coll Comp Sci & Technol, Guangzhou, Peoples R China

[3] Guangzhou Univ Chinese Med, Affiliated Hosp 2, Guangzhou, Peoples R China

[4] Sch Comp Sci & Technol, Harbin Inst Technol Shenzhen, L1819,Harbin Inst Technol Campus, Shenzhen 518055, Peoples R China

来源：

JMIR MEDICAL INFORMATICS | 2021年 / 9卷 / 10期

基金：

中国国家自然科学基金;

关键词：

health care; unstructured text; natural language processing; methodology; application;

D O I：

10.2196/23898

中图分类号：

R-058 [];

学科分类号：

摘要：

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".

引用

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