Development of an interpretable machine learning model for predicting prolonged hospital stay in patients with acute exacerbation of chronic obstructive pulmonary disease: a retrospective cohort study

Authors

Jinzhan Chen (ORCID: https://orcid.org/0009-0001-6778-3623)
Zhisheng Chen (ORCID: https://orcid.org/0000-0002-0854-2547)
Shuwen Yang (ORCID: https://orcid.org/0000-0002-3216-2376)
Hongni Jiang
Congyi Xie (ORCID: https://orcid.org/0009-0008-9013-3718)

Institutions

Fudan University (CN)
Zhongshan Hospital of Xiamen University (CN)

Publication Details

Journal: BMC Medical Informatics and Decision Making
Published: 2025-10-15
DOI: https://doi.org/10.1186/s12911-025-03220-3
Primary Topic: Chronic Obstructive Pulmonary Disease (COPD) Research
Type: article
Field-Weighted Citation Impact: 0.00

Funders

Xiamen Municipal Bureau of Science and Technology
Natural Science Foundation of Fujian Province

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article

Development of an interpretable machine learning model for predicting prolonged hospital stay in patients with acute exacerbation of chronic obstructive pulmonary disease: a retrospective cohort study

Jinzhan Chen, Zhisheng Chen, Shuwen Yang, Hongni Jiang et al.

Oct 15, 2025

BMC Medical Informatics and Decision Making

Chronic Obstructive Pulmonary Disease (COPD) Research

article

Development of an interpretable machine learning model for predicting prolonged hospital stay in patients with acute exacerbation of chronic obstructive pulmonary disease: a retrospective cohort study

Jinzhan Chen, Zhisheng Chen, Shuwen Yang, Hongni Jiang, Congyi Xie

October 15, 2025article en

Abstract

No abstract available for this paper.

BMC Medical Informatics and Decision MakingVol. 25(1)

Fudan University (CN), Zhongshan Hospital of Xiamen University (CN)

Xiamen Municipal Bureau of Science and Technology, Natural Science Foundation of Fujian Province

Openalex Percentile: Top 58%

Chronic Obstructive Pulmonary Disease (COPD) Research

DOI Open Access PDF OpenAlex

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