Model Based on Ultrasound Radiomics and Machine Learning to Preoperative Differentiation of Follicular Thyroid Neoplasm.

Journal: Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
PMID: 39555618

Abstract

OBJECTIVES: To evaluate the value of radiomics based on ultrasonography in differentiating follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) and construct a tool for preoperative noninvasive predicting FTC and FTA.

Authors

  • Yiwen Deng
    Department of Ultrasound, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
  • Qiao Zeng
    Jingtai Technology Co. Ltd Floor 4, No. 9, Yifenghua Industrial Zone, 91 Huaning Road, Longhua District Shenzhen Guangdong Province 518109 China.
  • Yu Zhao
    College of Agriculture, Shanxi Agricultural University, Taigu, Shanxi, China.
  • Zhen Hu
    Institute for Health Informatics.
  • Changmiao Zhan
    Department of Ultrasound, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
  • Liangyun Guo
    Department of Ultrasound, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
  • Binghuang Lai
    Department of Ultrasound, Ganzhou People's Hospital, Ganzhou, China.
  • Zhiping Huang
    Department of Ultrasound, Ganzhou People's Hospital, Ganzhou, China.
  • Zhiyong Fu
    Department of Ultrasound, Jiangxi Cancer Hospital & Institute, Jiangxi Clinical Research Center for Cancer, The Second Affiliated Hospital of Nanchang Medical College, Nanchang, China.
  • Chunquan Zhang
    Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.

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