Machine learning and SHAP value interpretation for predicting comorbidity of cardiovascular disease and cancer with dietary antioxidants.

Journal: Redox biology
PMID: 39700695

Abstract

OBJECTIVE: To develop and validate a machine learning model incorporating dietary antioxidants to predict cardiovascular disease (CVD)-cancer comorbidity and to elucidate the role of antioxidants in disease prediction.

Authors

  • Xiangjun Qi
    The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China.
  • Shujing Wang
    School of Biological Engineering, Dalian Polytechnic University No. 1st Qinggongyuan, Ganjingzi Dalian 116034 P. R. China liqian19820903@163.com +86-411-86323725 +86-411-86323725.
  • Caishan Fang
    Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, 610031, China; Yong Loo Lin School of Medicine, National University of Singapore, 117597, Singapore.
  • Jie Jia
    Department of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • Lizhu Lin
    The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510405, China; Guangdong Clinical Research Academy of Chinese Medicine, Guangzhou, 510405, China. Electronic address: gzucmlinlz@163.com.
  • Tianhui Yuan
    The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510405, China; Guangdong Clinical Research Academy of Chinese Medicine, Guangzhou, 510405, China. Electronic address: laura.yth@hotmail.com.

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