Machine learning models based on CT radiomics features for distinguishing benign and malignant vertebral compression fractures in patients with malignant tumors.

Journal: Acta radiologica (Stockholm, Sweden : 1987)
PMID: 39351680

Abstract

BACKGROUND: Radiomics has become an important tool for distinguishing benign and malignant vertebral compression fractures (VCFs). It is more clinically significant to concentrate on patients who have malignant tumors and differentiate between benign and malignant VCFs.

Authors

  • Yuan Wan
    Department of Radiology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, PR China.
  • Lei Miao
    School of Computer Science and Engineering, Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing 210096, China. Electronic address: miaolei@seu.edu.cn.
  • Huanhuan Zhang
    School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.
  • Yanmei Wang
    CAS Key Laboratory of Soft Matter Chemistry, Department of Polymer Science and Engineering, University of Science and Technology of China, Hefei 230026, PR China. Electronic address: wangyanm@ustc.edu.cn.
  • Xiao Li
    Department of Inner Mongolia Clinical Medicine College, Inner Mongolia Medical University, Hohhot, Inner Mongolia, China.
  • Meng Li
    Co-Innovation Center for the Sustainable Forestry in Southern China; Cerasus Research Center; College of Biology and the Environment, Nanjing Forestry University, Nanjing, China.
  • Li Zhang
    Department of Animal Nutrition and Feed Science, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.

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