Residential College | false |
Status | 已發表Published |
Natural Language Processing for Smart Healthcare | |
Zhou, Binggui1,2,3; Yang, Guanghua1; Shi, Zheng1,2; Ma, Shaodan2,3 | |
2024-03 | |
Source Publication | IEEE Reviews In Biomedical Engineering |
ISSN | 1937-3333 |
Volume | 17Pages:4-18 |
Abstract | Smart healthcare has achieved significant progress in recent years. Emerging artificial intelligence (AI) technologies enable various smart applications across various healthcare scenarios. As an essential technology powered by AI, natural language processing (NLP) plays a key role in smart healthcare due to its capability of analysing and understanding human language. In this work, we review existing studies that concern NLP for smart healthcare from the perspectives of technique and application. We first elaborate on different NLP approaches and the NLP pipeline for smart healthcare from the technical point of view. Then, in the context of smart healthcare applications employing NLP techniques, we introduce representative smart healthcare scenarios, including clinical practice, hospital management, personal care, public health, and drug development. We further discuss two specific medical issues, i.e., the coronavirus disease 2019 (COVID-19) pandemic and mental health, in which NLP-driven smart healthcare plays an important role. Finally, we discuss the limitations of current works and identify the directions for future works. |
Keyword | Natural Language Processing Smart Healthcare Artificial Intelligencence Nlp Techniques Healthcare Applications |
DOI | 10.1109/RBME.2022.3210270 |
URL | View the original |
Indexed By | SCIE |
Language | 英語English |
WOS Research Area | Engineering |
WOS Subject | Engineering, Biomedical |
WOS ID | WOS:001166967200012 |
Publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC445 HOES LANE, PISCATAWAY, NJ 08855-4141 |
Scopus ID | 2-s2.0-85139490480 |
Fulltext Access | |
Citation statistics | |
Document Type | Journal article |
Collection | DEPARTMENT OF ELECTROMECHANICAL ENGINEERING Faculty of Science and Technology THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU) DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING |
Corresponding Author | Yang, Guanghua; Ma, Shaodan |
Affiliation | 1.School of Intelligent Systems Science and Engineering, Jinan University, Zhuhai, China 2.State Key Laboratory of Internet of Things for Smart City, University of Macau, Macao, China 3.Department of Electrical and Computer Engineering, University of Macau, Macao 999078, Chi |
First Author Affilication | University of Macau |
Corresponding Author Affilication | University of Macau |
Recommended Citation GB/T 7714 | Zhou, Binggui,Yang, Guanghua,Shi, Zheng,et al. Natural Language Processing for Smart Healthcare[J]. IEEE Reviews In Biomedical Engineering, 2024, 17, 4-18. |
APA | Zhou, Binggui., Yang, Guanghua., Shi, Zheng., & Ma, Shaodan (2024). Natural Language Processing for Smart Healthcare. IEEE Reviews In Biomedical Engineering, 17, 4-18. |
MLA | Zhou, Binggui,et al."Natural Language Processing for Smart Healthcare".IEEE Reviews In Biomedical Engineering 17(2024):4-18. |
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