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Assessment of a Grad-CAM interpretable deep learning model for HAPE diagnosis: performance and pitfalls in severity stratification from chest radiographs

Crossref DOI link: https://doi.org/10.1186/s12911-025-03256-5

Published Online: 2025-10-30

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Yang, Ya

Yu, Hongmei

Xiang, Qijie

Wu, Jie

Li, Jianhao

Du, Feizhou

Yang, Yonglin

Wang, Peng
Funding

Funding for this research was provided by:

The General Hospital of Western Theater Command (Grant No. 2024-YGJS-B01)
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Text and Data Mining valid from 2025-10-30

Version of Record valid from 2025-10-30
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Article History

Received: 30 July 2025

Accepted: 16 October 2025

First Online: 30 October 2025

Declarations

:

: This retrospective study was approved by the Medical Ethics Committee of the General Hospital of Western Theater Command (Approval No: 2024EC7-ky037). The committee of the General Hospital of Western Theater Command waived the requirement for written informed consent to participate in this study, as per national regulations and institutional guidelines for retrospective analyses of anonymized imaging data. All methods were performed in accordance with the Declaration of Helsinki.

: Not applicable.

: The authors declare no competing interests.

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