Diagnostic Performance of Radiomics and Deep Learning to Identify Benign and Malignant Soft Tissue Tumors: A Systematic Review and Meta-analysis.

Journal: Academic radiology
Published Date: Apr 13, 2024

Abstract

RATIONALE AND OBJECTIVES: To systematically evaluate the application value of radiomics and deep learning (DL) in the differential diagnosis of benign and malignant soft tissue tumors (STTs).

Authors

  • Xinpeng Dai
    Department of Ultrasound, Hebei Medical University Third Hospital, Hebei, China.
  • Bingxin Zhao
    Department of Ultrasound, Hebei Medical University Third Hospital, Hebei, China.
  • Jiangnan Zang
    Hebei Medical University, Shijiazhuang, Hebei, China.
  • Xinying Wang
    Institute of Artificial Intelligence and Marine Robotics, School of Marine Electrical Engineering, Dalian Maritime University, Dalian, 116026, China. Electronic address: wxy1202@dlmu.edu.cn.
  • Zongjie Liu
    Department of Ultrasound, Hebei Medical University Third Hospital, Hebei, China.
  • Tao Sun
    Janssen Research & Development, LLC, Raritan, NJ, USA.
  • Hong Yu
    University of Massachusetts Medical School, Worcester, MA.
  • Xin Sui
    Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.

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