AI-driven prediction of insulin resistance in non-diabetic populations using minimal invasive tests: comparing models and criteria.

Journal: Diabetology & metabolic syndrome
Published Date: Aug 18, 2025

Abstract

BACKGROUND: Insulin resistance is a key precursor to diabetes and increases the risk of cardiovascular diseases. Traditional assessment methods rely on multiple invasive tests. Developing an AI model based on minimally invasive tests, especially using only fasting blood glucose as the invasive test, can promote health monitoring in non-diabetic populations, particularly for frequent routine checks.

Authors

  • Weihao Gao
    Tsinghua Shenzhen International Graduate School, Shenzhen, China.
  • Zhuo Deng
    Tsinghua Shenzhen International Graduate School, Shenzhen, China.
  • Zheng Gong
    Sino-Cellbiomed Institutes of Medical Cell & Pharmaceutical Proteins Qingdao University, Qingdao, Shandong, China. xblong2000@gmail.com.
  • Ziyi Jiang
  • Lan Ma
    School of Math and Statistic, Suzhou University, Suzhou, Anhui 23400, China.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals