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Radiomics-based kidney lesion classification: Mitigating batch effect with nested combat harmonization

delete2025-09-01
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OA
AI
N
Niloofar Ziasaeedi
Y
Yannick Lemaréchal
M
Mohsen Agharazii
V
Venkata Manem
P
Philippe Desprès
L
Leyla Ebrahimpour *
DOI：10.1002/mp.18070delete
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摘要

摘要

En 中文
CT成像的广泛应用提高了肾脏肿块的偶发检出率，需要准确区分良性与恶性结节。放射组学（Radiomics）为改善诊断提供了潜力；然而，其受限于成像参数（如层厚）的差异性，突显了有效标准化技术的必要性。
Keyword:
kidney cancer
machine learning
radiomics
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期刊

Medical Physics 封面图
Medical Physics
IF:
3.2
论文数:
3.7W
被引数:
3.2W

机构

C
centre de recherche du chu de québec
学者数:
18
论文数: 5
被引数: 0
U
Université Laval
学者数:
1.7K
论文数: 731
被引数: 0
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