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Deep learning and radiomics integration of photoacoustic/ultrasound imaging for non-invasive prediction of luminal and non-luminal breast cancer subtypes

Crossref DOI link: https://doi.org/10.1186/s13058-025-02113-7

Published Online: 2025-09-24

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

Authors

Wang, Mengyun

Mo, Sijie

Li, Guoqiu

Zheng, Jing

Wu, Huaiyu

Tian, Hongtian

Chen, Jing

Tang, Shuzhen

Chen, Zhijie

Xu, Jinfeng

Huang, Zhibin

Dong, Fajin
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Text and Data Mining valid from 2025-09-24

Version of Record valid from 2025-09-24
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Article History

Received: 31 October 2024

Accepted: 23 August 2025

First Online: 24 September 2025

Declarations

:

: This study has been approved by the Institutional Ethics Committee with approval number SYL-202161-02. All patients participating in the study have obtained informed consent.

: This study has obtained written informed consent from all research participants for the publication of their clinical details or identifiable data, including clinical images.

: The authors declare no competing interests.

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