Advanced pathological subtype classification of thyroid cancer using efficientNetB0.

Journal: Diagnostic pathology
PMID: 40055769

Abstract

BACKGROUND: Thyroid cancer is a prevalent malignancy requiring accurate subtype identification for effective treatment planning and prognosis evaluation. Deep learning has emerged as a valuable tool for analyzing tumor microenvironment features and distinguishing between pathological subtypes, yet the interplay between microenvironment characteristics and clinical outcomes remains unclear.

Authors

  • Hongpeng Guo
    Department of General Surgery, The Second Hospital Affiliated to Shenyang Medical College, No.64, Qishan West Road, Huanggu District, Shenyang, Liaoning, 110002, China.
  • Junjie Zhang
    Department of Immunology, School of Basic Medical Sciences, Anhui Medical University, Hefei, 230032, PR China.
  • You Li
    CFAR and I2R, Agency for Science, Technology and Research, Singapore.
  • Xinghe Pan
    Department of General Surgery, The Second Hospital Affiliated to Shenyang Medical College, No.64, Qishan West Road, Huanggu District, Shenyang, Liaoning, 110002, China. 15384708888@163.com.
  • Chenglin Sun
    Department of General Surgery, The Second Hospital Affiliated to Shenyang Medical College, No.64, Qishan West Road, Huanggu District, Shenyang, Liaoning, 110002, China. scl66661110@163.com.

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