A deep learning-based interpretable decision tool for predicting high risk of chemotherapy-induced nausea and vomiting in cancer patients prescribed highly emetogenic chemotherapy.

Journal: Cancer medicine
PMID: 37609808

Abstract

OBJECTIVE: This study aims to develop a risk prediction model for chemotherapy-induced nausea and vomiting (CINV) in cancer patients receiving highly emetogenic chemotherapy (HEC) and identify the variables that have the most significant impact on prediction.

Authors

  • Jingyue Zhang
    Department of Pharmacy, Tianjin Medical University General Hospital, Tianjin, China.
  • Xudong Cui
    School of Mathematics, Tianjin University, Tianjin, China.
  • Chong Yang
    Department of Pharmacy, Tianjin Medical University General Hospital, Tianjin, China.
  • Diansheng Zhong
    Department of Medical Oncology, Tianjin Medical University General Hospital, Tianjin, China.
  • Yinjuan Sun
    Department of Medical Oncology, Tianjin Medical University General Hospital, Tianjin, China.
  • Xiaoxiong Yue
    Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.
  • Gaoshuang Lan
    Department of Pharmacy, Tianjin Medical University General Hospital, Tianjin, China.
  • Linlin Zhang
    School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China.
  • Liangfu Lu
    Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.
  • Hengjie Yuan
    Department of Pharmacy, Tianjin Medical University General Hospital, Tianjin, China.

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