Addressing fractures that are hard to diagnose on imaging: Radiomics or deep learning?

Journal: La Radiologia medica
Published Date: Aug 7, 2025

Abstract

Fractures and their complications are recognized as major public health problems. Especially for occult fractures that are difficult to judge radiologically, timely and accurate diagnosis is particularly important for the treatment and prognosis of patients. In recent years, the successful application of radiomics and deep learning in medical diagnosis has shown great potential for providing more timely and accurate diagnostic methods for occult fractures. This review provides an introduction to radiomics and deep learning, summarizes their respective characteristics in detecting occult fractures, and subsequently conducts a detailed analysis on the potential value and future prospects of integrating these two techniques to develop an enhanced approach for prompt and precise detection of occult fractures.

Authors

  • Junlin Xu
    School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei 430065, China.
  • Xiaobo Wen
    The Affiliated Hospital of Qingdao University, Qingdao Medical College, Qingdao University, Qingdao 266071, China.
  • Yingchun Shao
    Department of Pharmacy, Qingdao Municipal Hospital, Qingdao, 266000, China.
  • Qing Liu
    School of Chemistry and Chemical Engineering, Shandong University of Technology, 255049, Zibo, PR China.
  • Sha Zhou
    The Affiliated Hospital of Qingdao University, Qingdao Medical College, Qingdao University, Qingdao 266071, China.
  • Li Jiyixuan
    The Affiliated Hospital of Qingdao University, Qingdao Medical College, Qingdao University, Qingdao, 266071, China.
  • Dan Wang
    Guangdong Pharmaceutical University Guangzhou Guangdong China.
  • Ying Yang
    Department of Endocrinology, The Affiliated Hospital of Yunnan University, Kunming, China.
  • Han Li
  • Linyuan Xue
    The Affiliated Hospital of Qingdao University, Qingdao Medical College, Qingdao University, Qingdao 266071, China.
  • Kunyue Xing
    Alliance Manchester Business School, The University of Manchester, Manchester M13 9PL, United Kingdom.
  • Xiaolin Wu
    Department of Orthopedics, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao 266003, China.
  • Dongming Xing
    The Affiliated Hospital of Qingdao University, Qingdao Medical College, Qingdao University, Qingdao 266071, China.

Keywords

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