Artificial intelligence model outperformed experienced clinicians in differentiating the aetiology of pneumonia on chest computed tomography: a retrospective study

This study presents a comprehensive classification closely aligned with pneumonia diagnosis in realistic clinical settings. We expect this method to be applied clinically to foster novel approaches to improve the accuracy in diagnosing pneumonia.

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Publication Details

Journal
Quantitative Imaging in Medicine and Surgery
Published
2025-12-31
DOI
https://doi.org/10.21037/qims-24-2129
Primary Topic
COVID-19 diagnosis using AI
Type
article
Field-Weighted Citation Impact
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article

Artificial intelligence model outperformed experienced clinicians in differentiating the aetiology of pneumonia on chest computed tomography: a retrospective study

Dongdong Gu, Yaozong Gao, Zhen Qian, Jue Pan et al.
Quantitative Imaging in Medicine and Surgery
COVID-19 diagnosis using AI
article

Artificial intelligence model outperformed experienced clinicians in differentiating the aetiology of pneumonia on chest computed tomography: a retrospective study

Dongdong Gu, Yaozong Gao, Zhen Qian, Jue Pan, Bijie Hu, Xi Ouyang, Ying Shao, Wei Shen, Meixia Wang, Tongjie Gu, Zhi Qiao, Wenting Jin
article en

Abstract

This study presents a comprehensive classification closely aligned with pneumonia diagnosis in realistic clinical settings. We expect this method to be applied clinically to foster novel approaches to improve the accuracy in diagnosing pneumonia.

Quantitative Imaging in Medicine and SurgeryVol. 16(1)
Sun Yat-sen University (CN), Fudan University (CN), Ningbo No. 2 Hospital (CN), Zhongshan Hospital of Xiamen University (CN), Zhongshan Hospital (CN), The First Affiliated Hospital, Sun Yat-sen University (CN), United Imaging Healthcare (China) (CN)
Good health and well-being
Openalex Percentile: Top 30%
COVID-19 diagnosis using AI
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