Imatinib adherence prediction using machine learning approach in patients with gastrointestinal stromal tumor.

Journal: Cancer
PMID: 39238433

Abstract

BACKGROUND: Nonadherence to imatinib is common in patients with gastrointestinal stromal tumor (GIST), which is associated with poor prognosis and financial burden. The primary aim of this study was to investigate the adherence rate in patients with GIST and subsequently develop a model based on machine learning (ML) and deep learning (DL) techniques to identify the associated factors and predict the risk of imatinib nonadherence.

Authors

  • Li Liu
    Metanotitia Inc., Shenzhen, China.
  • Ze Yu
    Beijing Medicinovo Technology Co. Ltd., Beijing, China.
  • Hefen Chen
    Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Zhujun Gong
    Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Xiao Huang
    Department of Anesthesiology, Beijing Chao-Yang Hospital, Capital Medical University, No. 8 Workers' Stadium South Road, Beijing 100020, Chaoyang Distinct, China.
  • Linhua Chen
    Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Ziying Fan
    Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Jinyuan Zhang
    Department of Colorectal and Anal Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
  • Jiannan Yan
    Beijing Medicinovo Technology Co., Ltd., Beijing, China.
  • Hongkun Tian
    Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Xiangyu Zeng
    Department of Plant Pathology, College of Agriculture, Guizhou University, Guiyang, Guizhou, PR China; Institute of Edible Mushroom, Guizhou University, Guiyang, PR China.
  • Zhiliang Chen
    Department of Critical Care Medicine, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362000, Fujian, China.
  • Peng Zhang
    Key Laboratory of Macromolecular Science of Shaanxi Province, School of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, Shaanxi 710062, China.
  • Hong Zhou
    Department of TCM Orthopedics & Traumatology, Gansu province hospital of TCM, Lanzhou, China.

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