Deep learning-based prediction of axillary pathological complete response in patients with breast cancer using longitudinal multiregional ultrasound

This study was supported by (1) Noncommunicable Chronic Diseases-National Science and Technology Major Project (No. 2024ZD0531100); (2) Key-Area Research and Development Program of Guangdong Province (No. 2021B0101420006); (3) National Natural Science Foundation of China (No. 82472051, 82471947, 82271941, 82272088); (4) National Science Foundation for Young Scientists of China (No. 82402270, 82202095, 82302190); (5) Guangzhou Municipal Science and Technology Planning Project (No. 2025A04J4773, 2025A04J4774); (6) the Natural Science Foundation of Guangdong Province of China (No. 2025A1515011607); (7) Medical Scientific Research Foundation of Guangdong Province of China (No. A2024403); (8) Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (No. 2022B1212010011); (9) Outstanding Youth Science Foundation of Yunnan Basic Research Project (No. 202401AY070001-316); (10) Innovative Research Team of Yunnan Province (No. 202505AS350013).

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Publication Details

Journal
EBioMedicine
Published
2025-08-27
DOI
https://doi.org/10.1016/j.ebiom.2025.105896
Citations
5
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
12.40
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article

Deep learning-based prediction of axillary pathological complete response in patients with breast cancer using longitudinal multiregional ultrasound

Jiayao Shi, Zhenhui Li, Yanfen Cui, Xiao‐Qing Pei et al.
5 citations
EBioMedicine
AI in cancer detection
12.40
article

Deep learning-based prediction of axillary pathological complete response in patients with breast cancer using longitudinal multiregional ultrasound

Jiayao Shi, Zhenhui Li, Yanfen Cui, Xiao‐Qing Pei, Lei Wu, Chunwang Huang, Yumeng Wang, Jiaxin Huang, Shufang Pei, Yu Liu, Ying Wang, Yuxiang Wang, Changhong Liang, Zejun Zhu, Mengxia Yao, Zaiyi Liu, Lifen Yan
article en
5 citations

Abstract

This study was supported by (1) Noncommunicable Chronic Diseases-National Science and Technology Major Project (No. 2024ZD0531100); (2) Key-Area Research and Development Program of Guangdong Province (No. 2021B0101420006); (3) National Natural Science Foundation of China (No. 82472051, 82471947, 82271941, 82272088); (4) National Science Foundation for Young Scientists of China (No. 82402270, 82202095, 82302190); (5) Guangzhou Municipal Science and Technology Planning Project (No. 2025A04J4773, 2025A04J4774); (6) the Natural Science Foundation of Guangdong Province of China (No. 2025A1515011607); (7) Medical Scientific Research Foundation of Guangdong Province of China (No. A2024403); (8) Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (No. 2022B1212010011); (9) Outstanding Youth Science Foundation of Yunnan Basic Research Project (No. 202401AY070001-316); (10) Innovative Research Team of Yunnan Province (No. 202505AS350013).

EBioMedicineVol. 119
Guangzhou University of Chinese Medicine (CN), Sun Yat-sen University (CN), Shanxi Medical University (CN), Kunming Medical University (CN), Key Laboratory of Guangdong Province (CN), First Affiliated Hospital of Guangzhou Medical University (CN), Shanxi Provincial Cancer Hospital (CN), Cancer Hospital of Chinese Academy of Medical Sciences (CN), Guangdong Academy of Medical Sciences (CN), Sun Yat-sen University Cancer Center (CN), Guangzhou Medical University (CN)
Openalex Percentile: Top 2%
AI in cancer detection
12.40
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