Diagnostic accuracy of machine learning-based magnetic resonance imaging models in breast cancer classification: a systematic review and meta-analysis.

Journal: World journal of surgical oncology
Published Date: Jun 11, 2025

Abstract

OBJECTIVE: This meta-analysis evaluates the diagnostic accuracy of machine learning (ML)-based magnetic resonance imaging (MRI) models in distinguishing benign from malignant breast lesions and explores factors influencing their performance.

Authors

  • Jupeng Zhang
    Department of Radiology, Affiliated Hospital of Youjiang Medical University for Nationalities, 533000, Baise, China (Q.W., C.H., J.Z., Z.Z., X.Z.); School of Laboratory Medicine, Youjiang Medical University for Nationalities, 533000, Baise, China (Q.W., J.Z., Z.Z.).
  • Qi Wu
    Endoscopy Center, Peking University Cancer Hospital and Institute, Beijing, China.
  • Peng Lei
    Department of Hepatobiliary Surgery, General Hospital of Ningxia Medical University, Yinchuan, China.
  • Xiqi Zhu
    Department of Radiology, Affiliated Hospital of Youjiang Medical University for Nationalities, 533000, Baise, China (Q.W., C.H., J.Z., Z.Z., X.Z.); Life Science and clinical Medicine Research Center, Affiliated Hospital of Youjiang Medical University for Nationalities, 533000, Baise, China (C.H., X.Z.). Electronic address: xiqi.zhu@163.com.
  • Baosheng Li
    Department of Radiation Oncology, Shandong Cancer Hospital, Shandong University, Jinan, 250117, China.

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