Prediction of recurrence risk factors in patients with early-stage cervical cancers by nomogram based on MRI handcrafted radiomics features and deep learning features: a dual-center study.

Journal: Abdominal radiology (New York)
Published Date: Nov 21, 2023

Abstract

PURPOSE: To establish and validate a deep learning radiomics nomogram (DLRN) based on intratumoral and peritumoral regions of MR images and clinical characteristics to predict recurrence risk factors in early-stage cervical cancer and to clarify whether DLRN could be applied for risk stratification.

Authors

  • Yajiao Zhang
    College of Medical Informatics, Chongqing Medical University, No.1 Medical College Road, Chongqing, China.
  • Chao Wu
  • Jinglong Du
    College of Medical Informatics, Chongqing Medical University, No.1 Medical College Road, Chongqing, China.
  • Zhibo Xiao
    State Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical University, Yixueyuan Road, Yuzhong District, Chongqing, 400016, China. 5894526@qq.com.
  • Furong Lv
    Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Yanbing Liu
    School of Management, Northwestern Polytechnical University, Xi'an 710129, Shanxi, China.

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