DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data.
Jiaqi LiuHengqiang ZhaoYu ZhengLin DongSen ZhaoYukuan HuangShengkai HuangTianyi QianJiali ZouShu LiuJun LiZihui YanYalun LiShuo ZhangXin HuangWenyan WangYiqun LiJie WangYue MingXiaoxin LiZeyu XingLing QinZhengye ZhaoZiqi JiaJiaxin LiGang LiuMenglu ZhangKexin FengJiang WuJianguo ZhangYongxin YangZhihong WuZhihua LiuJianming YingXin WangJianzhong SuXiang WangNan WuPublished in: Genome medicine (2022)
By considering the distinct endophenotypes associated with different CPGs in breast cancer patients, a phenotype-driven prediction model based on hierarchical neural network architecture was created for identification of hereditary breast cancer. The model achieved superior performance in identifying GPV carriers among Chinese breast cancer patients.