Machine Learning to Identify Metabolic Subtypes of Obesity: A Multi-Center Study.

Journal: Frontiers in endocrinology
PMID: 34335479

Abstract

BACKGROUND AND OBJECTIVE: Clinical characteristics of obesity are heterogenous, but current classification for diagnosis is simply based on BMI or metabolic healthiness. The purpose of this study was to use machine learning to explore a more precise classification of obesity subgroups towards informing individualized therapy.

Authors

  • Ziwei Lin
    Endocrinology and Metabolism Center, National Metabolic Management Center, Division of Metabolic Surgery for Obesity and Diabetes, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Wenhuan Feng
    Department of Endocrinology, Drum Tower Hospital Affiliated to Nanjing University Medical School, Nanjing, China.
  • Yanjun Liu
  • Chiye Ma
    Department of Bariatric and Metabolic Surgery, Shanghai East Hospital, Tongji University, Shanghai, China.
  • Dooman Arefan
    Department of Radiology, University of Pittsburgh, Pittsburgh, PA, United States.
  • Donglei Zhou
    Endocrinology and Metabolism Center, National Metabolic Management Center, Division of Metabolic Surgery for Obesity and Diabetes, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Xiaoyun Cheng
    Endocrinology and Metabolism Center, National Metabolic Management Center, Division of Metabolic Surgery for Obesity and Diabetes, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Jiahui Yu
    The Center of Gastrointestinal and Minimally Invasive Surgery, Chengdu Third People's Hospital, Southwest Jiaotong University, Chengdu, China.
  • Long Gao
    College of Computer, National University of Defense Technology, Changsha 410073, China; Department of Radiology, School of Medicine, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA 15260, USA.
  • Lei Du
    School of Mathematical Sciences, Dalian University of Technology, Chuangxinyuan Building, No.2 Linggong Road, Ganjingzi District, Dalian, 116024, Liaoning, China.
  • Hui You
    Endocrinology and Metabolism Center, National Metabolic Management Center, Division of Metabolic Surgery for Obesity and Diabetes, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Jiangfan Zhu
    Endocrinology and Metabolism Center, National Metabolic Management Center, Division of Metabolic Surgery for Obesity and Diabetes, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Dalong Zhu
    Department of Endocrinology, Drum Tower Hospital Affiliated to Nanjing University Medical School, Nanjing, China.
  • Shandong Wu
    Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, United States.
  • Shen Qu
    Endocrinology and Metabolism Center, National Metabolic Management Center, Division of Metabolic Surgery for Obesity and Diabetes, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.

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