Predictive models of hypertensive disorders in pregnancy based on support vector machine algorithm.

Abstract

Authors

• Lin Yang
  National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China.
• Ge Sun
  College of Life Science and Bioengineering, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, 100024, China.
• Anran Wang
  School of Computer Science and Technology, Dalian University of Technology, Dalian, China.
• Hongqing Jiang
  Haidian Maternal and Children Health Hospital, Beijing, 100080, China.
• Song Zhang
  College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
• Yimin Yang
• Xuwen Li
  College of Life Science and Bioengineering, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, 100024, China.
• Dongmei Hao
  College of Life Science and Bioengineering, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, 100024, China.
• Mingzhou Xu
  Beijing Aerospace ChangFeng Co. Ltd., Beijing, 100071, China.
• Jing Shao
  Institute of Electronics, Chinese Academy of Sciences, Beijing, 100190, China.

Keywords

External Resources