Machine learning models for predicting chemotherapy-induced adverse drug reactions in colorectal cancer patients.

Journal: Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Published Date: Jul 5, 2025

Abstract

BACKGROUND: Chemotherapy-induced adverse drug reactions (ADRs) are common in patients with colorectal cancer. We developed four machine learning models to predict chemotherapy-induced ADRs and assessed the performance. These models leverage high-dimensional data and non-linear relationships, offering better predictive accuracy than traditional methods.

Authors

  • Yingfei Wu
    Department of Gastroenterology, The Second Hospital of Shandong University, Jinan, Shandong 250033, China. Electronic address: 13563419287@163.com.
  • Wei Zhao
    Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, Jiangnan University, Wuxi 214122, Jiangsu Province, P. R. China. lxy@jiangnan.edu.cn zhuye@jiangnan.edu.cn.
  • Linxiao Zhang
    Department of Gastroenterology, The Second Hospital of Shandong University, Jinan, Shandong 250033, China. Electronic address: zhanglinxiao93@163.com.
  • Ying Wang
    Key Laboratory of Macromolecular Science of Shaanxi Province, School of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, Shaanxi 710062, China.
  • Ying Wen
    Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai 200241, China.
  • Lan Liu
    School of Statistics, University of Minnesota at Twin Cities.

Keywords

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