Construction and Application of a Traditional Chinese Medicine Syndrome Differentiation Model for Dysmenorrhea Based on Machine Learning.

Journal: Combinatorial chemistry & high throughput screening
Published Date: Jan 1, 2025

Abstract

BACKGROUND: Dysmenorrhea is one of the most common ailments affecting young and middle-aged women, significantly impacting their quality of life. Traditional Chinese Medicine (TCM) offers unique advantages in treating dysmenorrhea. However, an accurate diagnosis is essential to ensure correct treatment. This research integrates the age-old wisdom of TCM with modern Machine Learning (ML) techniques to enhance the precision and efficiency of dysmenorrhea syndrome differentiation, a pivotal process in TCM diagnostics and treatment planning.

Authors

  • Limin Zhang
    School of Information, University of Arizona, 1103 E. Second Street, Tucson, AZ 85705, USA.
  • Jianing You
    The Faculty of Applied Science and Engineering, University of Toronto, Toronto, Ontario, Canada.
  • Yiqing Huang
    College of Basic Medical, Shanxi University of Chinese Medicine, Taiyuan, Shanxi, China.
  • Ruiqi Jing
    The Faculty of Applied Science and Engineering, University of Toronto, Toronto, Ontario, Canada.
  • Yifei He
    Department of EECS, University of Michigan, Ann Arbor, Michigan, USA.
  • Yujie Wen
    College of Basic Medical, Shanxi University of Chinese Medicine, Taiyuan, Shanxi, China.
  • Lulu Zheng
    School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.
  • Yong Zhao
    a School of Mathematics and Information Science , Henan Polytechnic University , Jiaozuo 454000 , People's Republic of China.

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