The result prediction of fluorescence in situ hybridization for breast cancer patients based on machine learning and deep learning models: a multicenter study

Abstract Objective To develop and validate a multicenter ultrasound-based predictive model for fluorescence in situ hybridization (FISH) results in HER2 (2+) breast cancer patients, aiming to provide a convenient and cost-effective tool to support clinical decision-making. Materials and methods In t...

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Principais autores:	Cong Jiang, Dong Chen, Xiao Yu, Shentao Zhang, Yuting Xiu, Ningbin Luo, Jingjing Wu, Xuefang Zhang, Man Chen, Dechun Yang, Ziyu Zhu, Yuanxi Huang, Shipeng Ning, Shicong Tang
Formato:	Artigo
Idioma:	Inglês
Publicado:	BMC 2026-03-01
Series:	Cancer Imaging
Assuntos:	FISH ViT Breast cancer Machine learning
Acceso en liña:	https://doi.org/10.1186/s40644-026-01015-x
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