Development and validation of clinical-radiomics deep learning model based on MRI for endometrial cancer molecular subtypes classification.

Journal: Insights into imaging
Published Date:

Abstract

OBJECTIVES: This study aimed to develop and validate a clinical-radiomics deep learning (DL) model based on MRI for endometrial cancer (EC) molecular subtypes classification.

Authors

  • Wenyi Yue
    Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
  • Ruxue Han
    Department of Gynecology and Obstetrics, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
  • Haijie Wang
    Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China.
  • Xiaoyun Liang
    The School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, People's Republic of China.
  • He Zhang
    College of Natural Resources and Environment, Northwest A&F University, Yangling, 712100, Shaanxi, PR China; Key Laboratory of Plant Nutrition and the Agri-environment in Northwest China, Ministry of Agriculture and Rural Affairs, Yangling, 712100, Shaanxi, PR China.
  • Hua Li
    Department of Stomatology, The First Medical Center Chinese PLA General Hospital Beijing China.
  • Qi Yang
    Department of Radiology, The First Hospital of Jilin University, No.1, Xinmin Street, Changchun 130021, China (Y.W., M.L., Z.M., J.W., K.H., Q.Y., L.Z., L.M., H.Z.).

Keywords

No keywords available for this article.