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人工智能技术在中国基层医疗机构慢性阻塞性肺疾病早期筛查中的应用及展望。

Application and Prospects of Artificial Intelligence Technology in Early Screening of Chronic Obstructive Pulmonary Disease at Primary Healthcare Institutions in China.

机构信息

Department of General Practice, Donghuashi Community Health Service Center, Beijing, People's Republic of China.

出版信息

Int J Chron Obstruct Pulmon Dis. 2024 May 14;19:1061-1067. doi: 10.2147/COPD.S458935. eCollection 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.

摘要

慢性阻塞性肺疾病(COPD)是全球主要的健康威胁疾病之一,在中国尤为如此,其具有较高的患病率和死亡率。早期诊断对于控制疾病进展和改善患者预后至关重要。然而,由于缺乏明显的早期症状,COPD 的知晓率和诊断率仍然较低。在此背景下,基层医疗机构在识别高危人群和早期诊断方面发挥着关键作用。随着人工智能(AI)技术的发展,其在提高 COPD 筛查的效率和准确性方面具有明显的潜力。本文讨论了 COPD 高危人群的特征、当前的筛查方法,以及 AI 技术在筛查各个方面的应用。还强调了 AI 应用中的挑战,如数据隐私、算法准确性和可解释性。提出了一些改进建议,如增强 AI 技术的传播、提高数据质量、促进跨学科合作以及加强政策和资金支持,旨在进一步提高 AI 技术在我国基层医疗机构 COPD 筛查中的效果和前景。

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