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Application and Prospects of Artificial Intelligence Technology in Early Screening of Chronic Obstructive Pulmonary Disease at Primary Healthcare Institutions in China.
- Source :
-
International journal of chronic obstructive pulmonary disease [Int J Chron Obstruct Pulmon Dis] 2024 May 14; Vol. 19, pp. 1061-1067. Date of Electronic Publication: 2024 May 14 (Print Publication: 2024). - Publication Year :
- 2024
-
Abstract
- Chronic Obstructive Pulmonary Disease (COPD), as one of the major global health threat diseases, particularly in China, presents a high prevalence and mortality rate. Early diagnosis is crucial for controlling disease progression and improving patient prognosis. However, due to the lack of significant early symptoms, the awareness and diagnosis rates of COPD remain low. Against this background, primary healthcare institutions play a key role in identifying high-risk groups and early diagnosis. With the development of Artificial Intelligence (AI) technology, its potential in enhancing the efficiency and accuracy of COPD screening is evident. This paper discusses the characteristics of high-risk groups for COPD, current screening methods, and the application of AI technology in various aspects of screening. It also highlights challenges in AI application, such as data privacy, algorithm accuracy, and interpretability. Suggestions for improvement, such as enhancing AI technology dissemination, improving data quality, promoting interdisciplinary cooperation, and strengthening policy and financial support, aim to further enhance the effectiveness and prospects of AI technology in COPD screening at primary healthcare institutions in China.<br />Competing Interests: The author reports no conflicts of interest in this work.<br /> (© 2024 Yang.)
- Subjects :
- Humans
China epidemiology
Risk Factors
Diagnosis, Computer-Assisted
Lung physiopathology
Risk Assessment
Reproducibility of Results
Prognosis
Pulmonary Disease, Chronic Obstructive diagnosis
Pulmonary Disease, Chronic Obstructive epidemiology
Early Diagnosis
Primary Health Care
Artificial Intelligence
Predictive Value of Tests
Mass Screening methods
Subjects
Details
- Language :
- English
- ISSN :
- 1178-2005
- Volume :
- 19
- Database :
- MEDLINE
- Journal :
- International journal of chronic obstructive pulmonary disease
- Publication Type :
- Academic Journal
- Accession number :
- 38765765
- Full Text :
- https://doi.org/10.2147/COPD.S458935