Machine learning for detection of diffusion abnormalities-related respiratory changes among normal, overweight, and obese individuals based on BMI and pulmonary ventilation parameters: an observational study.

Journal: BMC medical informatics and decision making
Published Date: Jul 1, 2025

Abstract

BACKGROUND: The integration of machine learning (ML) algorithms enables the detection of diffusion abnormalities-related respiratory changes in individuals with normal body mass index (BMI), overweight, and obesity based on BMI and pulmonary ventilation parameters. We evaluated the effectiveness of various supervised ML algorithms and identified the optimal configurations for these applications.

Authors

  • Xin-Yue Song
    Department of Respiratory and Critical Care Medicine, West China School of Medicine and West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, China.
  • Xin-Peng Xie
    College of Electrical Engineering and Automation, Sichuan University, Chengdu, 610065, China.
  • Wen-Jing Xu
    Department of Respiratory and Critical Care Medicine, West China School of Medicine and West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, China.
  • Yu-Jia Cao
    Department of Respiratory and Critical Care Medicine, West China School of Medicine, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, China.
  • Bin-Miao Liang
    Department of Respiratory and Critical Care Medicine, West China School of Medicine and West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, China. liangbinmiao@163.com.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals