Health Natural Language Processing: Methodology Development and Applications
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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".
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Traditional automated extraction of structured data elements from medical notes has relied on medical NLP using rule-based or machine-learning approaches or a combination of both.
“Traditionally, the automated extraction of structured data elements from medical notes has relied on medical natural language processing (NLP) using rule-based or machine-learning approaches or a combination of both9,10.”
From A critical assessment of using ChatGPT for extracting structured data from clinical notes (2024) · cites this paper as [9]
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References 16 · Cited by 48
- Authors
- Hao, T., Huang, Z., Liang, L., Weng, H., & Tang, B.
- Affiliations
- South China Normal University (CN)
- Zhejiang University (CN)
- Guangzhou University of Chinese Medicine (CN)
- Harbin Institute of Technology (CN)
- Corresponding author
- Tang, Buzhou
- Venue
- JMIR Medical Informatics
- Publisher
- JMIR Publications Inc.
- Published
- 2021-10-21
- Volume
- 9
- Issue
- 10
- Pages
- e23898
- ISSN
- 2291-9694 (ISSN-L)
- PMC
- PMC8569540
- OpenAlex
- W3157411108
- Cited by
- 48
- References
- 16
- Citations by year
- 2026: 5 · 2025: 19 · 2024: 12 · 2023: 7 · 2022: 5
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR Medical Informatics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- National Natural Science Foundation of China (U1813215, 2019A1515011158, 61876052, 61672450, 61772146, 61871141)
- Natural Science Foundation of Guangdong Province (2019A1515011158, 61772146, 2015B010131010)
- Harbin Institute of Technology (HIT.NSRIF.2017052)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
- Keywords
- clinical text mining, discharge summaries, online health discussions, inclusion and exclusion criteria, medical data processing
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