An Integrated Radiopathomics Machine Learning Model to Predict Pathological Response to Preoperative Chemotherapy in Gastric Cancer.

Journal: Academic radiology
Published Date: Aug 30, 2024

Abstract

RATIONALE AND OBJECTIVES: Accurately predicting the pathological response to chemotherapy before treatment is important for selecting the appropriate treatment groups, formulating individualized treatment plans, and improving the survival rates of patients with gastric cancer (GC).

Authors

  • Yaolin Song
    Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Shunli Liu
    Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, 266003, Shandong, China.
  • Xinyu Liu
    Institute of Medical Technology, Peking University Health Science Center, Beijing, China.
  • Huiqing Jia
    Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Hailei Shi
    Department of Pathology, The Affiliated Hospital of Qingdao University, No.16 Jiangsu Road, Qingdao, China.
  • Xianglan Liu
    Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Dapeng Hao
    Department of Radiology, The Affiliated Hospital of Qingdao University, Shinan Jiangsu 16 Rd, Qingdao, Shandong 266003, China.
  • Hexiang Wang
    Department of Radiology, The Affiliated Hospital of Qingdao University, Shinan Jiangsu 16 Rd, Qingdao, Shandong 266003, China.
  • Xiaoming Xing
    Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China.

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