Artificial intelligence assisted nutritional risk evaluation model for critically ill patients: Integration of explainable machine learning in intensive care nutrition.

Journal: Asia Pacific journal of clinical nutrition
Published Date: Jun 1, 2025

Abstract

BACKGROUND AND OBJECTIVES: Critically ill patients require individualized nutrition support, with assessment tools like Nutrition Risk Screening 2002 and Nutrition Risk in the Critically Ill scores. Challenges in continu-ous nutrition care prompt the need for innovative solutions. This study develops an artificial intelligence assisted nutrition risk evaluation model using explainable machine learning to support intensive care unit dietitians.

Authors

  • Chao-Hsiu Chen
    Department of Food and Nutrition, Taichung Veterans General Hospital, Taichung, Republic of China.
  • Kai-Chih Pai
    College of Engineering, Tunghai University, No. 1727, Sec. 4, Taiwan Boulevard, Xitun District, Taichung City, 407224, Taiwan, ROC. kcpai@thu.edu.tw.
  • Hui-Min Hsieh
    Center for Big Data Research, Kaohsiung Medical University, Kaohsiung, Taiwan.
  • Yi-Jui Chan
    Department of Food and Nutrition, Taichung Veterans General Hospital, Taichung, Republic of China.
  • Hsiao-Lin Hsu
    Department of Food and Nutrition, Taichung Veterans General Hospital, Taichung, Republic of China.
  • Chen-Yu Wang
    Department of Digestive Tumor, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.

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