Development and validation of preeclampsia predictive models using key genes from bioinformatics and machine learning approaches.

Abstract

Authors

• Qian Li
  Emergency and Critical Care Center, Department of Emergency Medicine, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, China.
• Xiaowei Wei
  Reproductive Medicine Center, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
• Fan Wu
  Department of Product Design, Dalian Polytechnic University, Dalian 116034, China.
• Chuanmei Qin
  Reproductive Medicine Center, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
• Junpeng Dong
  Reproductive Medicine Center, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
• Cailian Chen
  Department of Automation, Shanghai Jiao Tong University, Shanghai, China.
• Yi Lin
  Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.

Keywords

External Resources