机构:[1]Department of General Surgery, The Second Affiliated Hospital of Shanghai University (Wenzhou Central Hospital), Wenzhou, Zhejiang, 325000, China[2]School of Digital Media, Shenzhen Institute of Information Technology, Shenzhen, 518172, China[3]College of Computer Science, Sichuan University, Chengdu, Sichuan, 610065, China
Guangdong provincial ordinary
university characteristic innovation project KJ2021C006.
语种:
外文
PubmedID:
中科院(CAS)分区:
出版当年[2023]版:
大类|2 区医学
小类|1 区生物学1 区数学与计算生物学2 区计算机:跨学科应用2 区工程:生物医学
最新[2023]版:
大类|2 区医学
小类|1 区生物学1 区数学与计算生物学2 区计算机:跨学科应用2 区工程:生物医学
第一作者:
第一作者机构:[1]Department of General Surgery, The Second Affiliated Hospital of Shanghai University (Wenzhou Central Hospital), Wenzhou, Zhejiang, 325000, China
通讯作者:
推荐引用方式(GB/T 7714):
Li Wencai,Yang Daqing,Ma Chao,et al.Identifying novel disease categories through divergence optimization: An approach to prevent misdiagnosis in medical imaging[J].Computers in biology and medicine.2023,165:107403.doi:10.1016/j.compbiomed.2023.107403.
APA:
Li Wencai,Yang Daqing,Ma Chao&Liu Lei.(2023).Identifying novel disease categories through divergence optimization: An approach to prevent misdiagnosis in medical imaging.Computers in biology and medicine,165,
MLA:
Li Wencai,et al."Identifying novel disease categories through divergence optimization: An approach to prevent misdiagnosis in medical imaging".Computers in biology and medicine 165.(2023):107403