An Explainable Multimodal Artificial Intelligence Model Integrating Histopathological Microenvironment and EHR Phenotypes for Germline Genetic Testing in Breast Cancer

Abstract Genetic testing for pathogenic germline variants is critical for the personalized management of high‐risk breast cancers, guiding targeted therapies and cascade testing for at‐risk families. In this study, MAIGGT (Multimodal Artificial Intelligence Germline Genetic Testing) is proposed, a d...

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Bibliographic Details
Main Authors:	Zijian Yang, Changyuan Guo, Jiayi Li, Yalun Li, Lei Zhong, Pengming Pu, Tongxuan Shang, Lin Cong, Yongxin Zhou, Guangdong Qiao, Ziqi Jia, Hengyi Xu, Heng Cao, Yansong Huang, Tianyi Liu, Jian Liang, Jiang Wu, Dongxu Ma, Yuchen Liu, Ruijie Zhou, Xiang Wang, Jianming Ying, Meng Zhou, Jiaqi Liu
Format:	Article
Language:	English
Published:	Wiley 2025-08-01
Series:	Advanced Science
Subjects:	BRCA1/2 breast cancer deep learning electronic health records tumor microenvironment whole‐slide image
Online Access:	https://doi.org/10.1002/advs.202502833
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An Explainable Multimodal Artificial Intelligence Model Integrating Histopathological Microenvironment and EHR Phenotypes for Germline Genetic Testing in Breast Cancer

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