Using machine learning for early detection of chronic obstructive pulmonary disease: a narrative review
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作者:
Shen, Xueting
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Nanchang Univ, Dept Gen Surg, Affiliated Hosp 1, Nanchang 330000, Peoples R ChinaNanchang Univ, Dept Gen Surg, Affiliated Hosp 1, Nanchang 330000, Peoples R China
Shen, Xueting
[1
]
Liu, Huanbing
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Nanchang Univ, Dept Gen Surg, Affiliated Hosp 1, Nanchang 330000, Peoples R China
Nanchang Univ, Affiliated Hosp 1, Dept Gen Practice, Nanchang 330000, Peoples R ChinaNanchang Univ, Dept Gen Surg, Affiliated Hosp 1, Nanchang 330000, Peoples R China
Liu, Huanbing
[1
,2
]
机构:
[1] Nanchang Univ, Dept Gen Surg, Affiliated Hosp 1, Nanchang 330000, Peoples R China
[2] Nanchang Univ, Affiliated Hosp 1, Dept Gen Practice, Nanchang 330000, Peoples R China
Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory disease and ranks third in global mortality rates, imposing a significant burden on patients and society. This review looks at recent research, both domestically and abroad, on the application of machine learning (ML) for early COPD screening. The review discusses the practical application, key optimization points, and prospects of ML techniques in early COPD screening. The aim is to establish a scientific foundation and reference framework for future research and the development of screening strategies.