Organ-system-based subclassification of preeclampsia using machine learning predicts pregnancy outcomes.

Abstract

Authors

• Yanhong Xu
  College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University Fujian Maternity and Child Health Hospital, No. 18 Daoshan Road, Gulou District, Fuzhou, Fujian, PR China.
• Yizheng Zu
  The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, Jiangsu, PR China.
• Xiaosi Lu
  College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University Fujian Maternity and Child Health Hospital, No. 18 Daoshan Road, Gulou District, Fuzhou, Fujian, PR China.
• Yiping Wang
  Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things, Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors, State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen 518060, China.
• Jiaying Zheng
  College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University Fujian Maternity and Child Health Hospital, No. 18 Daoshan Road, Gulou District, Fuzhou, Fujian, PR China.
• Xia Xu
  College of Food Science and Technology, Zhejiang University of Technology, Hangzhou 310014, PR China; Zhejiang Key Laboratory of Green, Low-carbon and Efficient Development of Marine Fishery Resources, Hangzhou 310014, PR China; National R&D Branch Center for Pelagic Aquatic Products Processing (Hangzhou), Hangzhou 310014, PR China. Electronic address: xuxia@zjut.edu.cn.
• Jianying Yan
  Department of Obstetrics and Gynecology, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University Fujian Maternity and Child Health Hospital, Fuzhou, China. yanjy2019@fjmu.edu.cn.

Keywords

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