DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data

Liu, JQ; Zhao, HQ; Zheng, Y; Dong, L; Zhao, S; Huang, YK; Huang, SK; Qian, TY; Zou, JL; Liu, S; Li, J; Yan, ZH; Li, YL; Zhang, S; Huang, X; Wang, WY; Li, YQ; Wang, J; Ming, Y; Li, XX; Xing, ZY; Qin, L; Zhao, ZY; Jia, ZQ; Li, JX; Liu, G; Zhang, ML; Feng, KX; Wu, J; Zhang, JG; Yang, YX; Wu, ZH; Liu, ZH; Ying, JM; Wang, X; Su, JZ; Wang, X; Wu, N

Wang, X (通讯作者),Chinese Acad Med Sci & Peking Union Med Coll, Natl Canc Ctr, Dept Breast Surg Oncol, Natl Clin Res Ctr Canc,Canc Hosp, Beijing 100021, Peoples R China.;Su, JZ (通讯作者),Wenzhou Med Univ, Inst Biomed Big Data, Wenzhou 325027, Peoples R China.;Wu, N (通讯作者),Peking Union Med Coll & Chinese Acad Med Sci, Peking Union Med Coll Hosp, Dept Orthoped Surg, Beijing 100730, Peoples R China.;Wu, N (通讯作者),Peking Union Med Coll & Chinese Acad Med Sci, Peking Union Med Coll Hosp, Beijing Key Lab Gen

GENOME MEDICINE, 2022; 14 (1):

Abstract

Background: Identifying breast cancer patients with DNA repair pathway-related germline pathogenic variants (GPVs) is important for effectively employ......

Full Text Link