Health Natural Language Processing: Methodology Development and Applications

Tianyong Hao; Zhengxing Huang; Likeng Liang; Heng Weng; Buzhou Tang

doi:10.2196/23898

Health Natural Language Processing: Methodology Development and Applications

JMIR Med Inform. 2021 Oct 21;9(10):e23898. doi: 10.2196/23898.

Authors

Tianyong Hao¹, Zhengxing Huang², Likeng Liang¹, Heng Weng³, Buzhou Tang⁴

Affiliations

¹ School of Computer Science, South China Normal University, Guangzhou, China.
² College of Computer Science and Technology, Zhejiang University, Guangzhou, China.
³ The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, China.
⁴ School of Computer Science and Technology, Harbin Institute of Technology Shenzhen, Shenzhen, China.

PMID: 34673533
PMCID: PMC8569540
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".

Keywords: application; health care; methodology; natural language processing; unstructured text.

©Tianyong Hao, Zhengxing Huang, Likeng Liang, Heng Weng, Buzhou Tang. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 21.10.2021.

Publication types

Editorial