Predicting risk of overweight or obesity in Chinese preschool-aged children using artificial intelligence techniques.

Journal: Endocrine
PMID: 35583845

Abstract

OBJECTIVES: We adopted the machine-learning algorithms and deep-learning sequential model to determine and optimize most important factors for overweight and obesity in Chinese preschool-aged children.

Authors

  • Qiong Wang
    Beijing Meiling Biotechnology Corporation, Beijing, 102600, PR China.
  • Min Yang
    College of Food Science and Engineering, Ocean University of China, Qingdao, 266003, Shandong, China.
  • Bo Pang
    College of Water Sciences, Beijing Normal University; Beijing 100875, China; Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China. Electronic address: pb@bnu.edu.cn.
  • Mei Xue
    Beijing Engineering Research Center of Diagnosis and Treatment of Respiratory and Critical Care Medicine, Beijing Chaoyang Hospital, Beijing 100043, China.
  • Yicheng Zhang
    Department of Hematology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
  • Zhixin Zhang
    School of Mathematics Sciences, Anhui University, Hefei 230601, China.
  • Wenquan Niu
    Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing 100029, China. Electronic address: niuwenquan_shcn@163.com.

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