The ontology framework and challenges of smart healthcare system transformation using natural language processing and latent Dirichlet allocation.
Objectives: This article aims to develop the ontology framework of smart healthcare system and identify the challenges to construct the smart healthcare system. The ontology framework provides both academics and practitioners a reference to understand and transform the healthcare system. Methods: Th...
| Published in: | Health Informatics Journal Vol. 31; no. 3; pp. 1 - 20 |
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| Main Authors: | , , , |
| Format: | equations & formulas pictorial research tables/charts Journal Article |
| Published: |
Sage Publications Inc.
Jul-Sep2025
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188361407&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188361407 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14604582 EJK jtl: Health Informatics Journal issn: 14604582 maglogo: Y pubinfo: dt: Jul-Sep2025 vid: 31 iid: 3 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 188361407 188361407 188361407 10.1177/14604582251381280 188361407 ppf: 1 ppct: 19 formats: tig: atl: The ontology framework and challenges of smart healthcare system transformation using natural language processing and latent Dirichlet allocation. aug: au: Zhao, Shuyan Zhong, Hua Ge, Beibei Zhao, Xiaojing affil: School of Management, Beijing Institute of Technology, Beijing, Peoples R China sug: subj: Health Information Systems Natural Language Processing Methods Ontologies Methods Artificial Intelligence Methods Health Care Reform Medical Informatics Human Hospitals Data Mining Information Retrieval Decision Support Systems, Clinical Data Security Personnel Management Health Policy Quality Assessment Organizational Change Funding Source ab: Objectives: This article aims to develop the ontology framework of smart healthcare system and identify the challenges to construct the smart healthcare system. The ontology framework provides both academics and practitioners a reference to understand and transform the healthcare system. Methods: The publications in the area of the smart healthcare system were extracted from WOS core collection database. Latent Dirichlet Allocation (LDA) was employed to find subjects of publications. Natural language processing (NLP) was used to extract entities from topics explored based on LDA. The developed ontology framework of the smart healthcare system was then presented in OWL format using Protégé software. The challenges in transforming towards the smart healthcare system were identified based on the developed ontology framework. Results: Fourteen challenges are identified through the ontology framework developed by NLP and LDA, including poor system interoperability, data security and data sharing, low adoption of data standards and data scalability, etc. These challenges provide a reference for future healthcare workers to deal with possible risks and difficulties. Conclusions: The ontology framework developed by NLP and LDA provides a unified description and structured knowledge in smart healthcare system, and provides valuable working methods and management basis for scholars and medical workers. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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