首页> The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians> Predictive efficacy of machine-learning algorithms on intrahepatic cholestasis of pregnancy based on clinical and laboratory indicators.

Predictive efficacy of machine-learning algorithms on intrahepatic cholestasis of pregnancy based on clinical and laboratory indicators.

导出 LinkOut

翻译打印收藏纠错

第一作者： Jianhu,He

第一单位： Information Center, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.;Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.

作者： Jianhu,He ^[1] ; Xiaojun,Zhu ^[2] ; Xuan,Yang ^[3] ; Hui,Wang ^[4]

作者单位： Information Center, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.;Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China. ^[1] Department of Obstetrics, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China. ^[2] Information Center, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China. ^[3] Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China. ^[4]

关键词 Arya Privacy Computing Platform Intrahepatic cholestasis of pregnancy machine learning maternal health predictive efficacy sequential data analysis