Thyroid nodule classification in ultrasound imaging using deep transfer learning.

Journal: BMC cancer
PMID: 40133868

Abstract

BACKGROUND: The accurate diagnosis of thyroid nodules represents a critical and frequently encountered challenge in clinical practice, necessitating enhanced precision in diagnostic methodologies. In this study, we investigate the predictive efficacy of distinguishing between benign and malignant thyroid nodules by employing traditional machine learning algorithms and a deep transfer learning model, aiming to advance the diagnostic paradigm in this field.

Authors

  • Yan Xu
    Department of Nephrology, Suzhou Ninth People's Hospital, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou, China.
  • Mingmin Xu
    College of Agriculture, Nanjing Agricultural University, Jiangsu, 210095, Nanjing, China.
  • Zhe Geng
    Department of Ultrasound, Zhejiang Rongjun Hospital, No.309 Shuangyuan Road, Jiaxing, 314001, China.
  • Jie Liu
    School of Bioscience and Bioengineering, South China University of Technology, Guangzhou, China.
  • Bin Meng
    Department of Pathology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin; Tianjin's Clinical Research Center for Cancer, Tianjin Medical University, Ministry of Education, Tianjin 300060, China.

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