Novel machine learning model for predicting cancer drugs' susceptibilities and discovering novel treatments.

Journal: Journal of biomedical informatics
Published Date: Dec 12, 2024

Abstract

BACKGROUND AND OBJECTIVE: Timely treatment is crucial for cancer patients, so it's important to administer the appropriate treatment as soon as possible. Because individuals can respond differently to a given drug due to their unique genomic profiles, we aim to use their genomic information to predict how various drugs will affect them and determine the best course of treatment.

Authors

  • Xiaowen Cao
    School of Artificial Intelligence, Hebei University of Technology, Tianjin, China; Department of Mathematics and Statistics, University of Victoria, Victoria, Canada.
  • Li Xing
    WuXi AppTec Co., Ltd, Shanghai, China.
  • Hao Ding
  • He Li
    National Soybean Processing Industry Technology Innovation Center, Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Technology and Business University Beijing 100048 China lihe@btbu.edu.cn liuxinqi@btbu.edu.cn.
  • Yushan Hu
    Department of Mathematics and Statistics, University of Victoria, Victoria, Canada.
  • Yao Dong
    School of Artificial Intelligence, Hebei University of Technology, Tianjin, China; Department of Mathematics and Statistics, University of Victoria, Victoria, Canada.
  • Hua He
    State Key Laboratory of Heavy Oil Processing and College of Chemistry and Chemical Engineering, China University of Petroleum (East China), Qingdao 266580, China.
  • Junhua Gu
    School of Artificial Intelligence, Hebei University of Technology, Tianjin, China. Electronic address: jhgu@hebut.edu.cn.
  • Xuekui Zhang
    Department of Mathematics and Statistics, University of Victoria, Victoria, Canada. Electronic address: Xuekui@uvic.ca.

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