A data-driven machine learning algorithm to predict the effectiveness of inulin intervention against type II diabetes.

Journal: Frontiers in nutrition
Published Date: Jan 7, 2025

Abstract

INTRODUCTION: The incidence of type 2 diabetes mellitus (T2DM) has increased in recent years. Alongside traditional pharmacological treatments, nutritional therapy has emerged as a crucial aspect of T2DM management. Inulin, a fructan-type soluble fiber that promotes the growth of probiotic species like and , is commonly used in nutritional interventions for T2DM. However, it remains unclear which type of T2DM patients are suitable for inulin intervention. The aim of this study was to predict the effectiveness of inulin treatment for T2DM using a machine learning model.

Authors

  • Shuheng Yang
    School of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China.
  • Ralf Weiskirchen
    Institute of Molecular Pathobiochemistry, Experimental Gene Therapy and Clinical Chemistry (IFMPEGKC), RWTH University Hospital Aachen, Aachen, Germany.
  • Wenjing Zheng
    School of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China.
  • Xiangxu Hu
    School of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China.
  • Aibiao Zou
    Research Center of Medical Nutrition Therapy, Cross-strait Tsinghua Research Institute, Xiamen, China.
  • Zhiguo Liu
    School of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China.
  • Hualin Wang
    School of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China.

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