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将基于人工智能的转移学习模型应用于贝塞斯达系统的甲状腺细胞病理学应用

Pranab Dey1, Rajiv Savala2, Uma Nahar Saikia3

  • 1Department of Cytology, Post Graduate Institute of Medical Education and Research, Chandigarh, India.

Cytopathology : official journal of the British Society for Clinical Cytology
|December 9, 2025
PubMed
概括

这项研究表明,整体转移学习使用贝塞斯达甲状腺细胞病理报告系统 (TBSRTC) 准确地对甲状腺细针吸收细胞学 (FNAC) 进行了分类. 该模型在良性和恶性甲状腺病例中表现出强大的预测准确性.

关键词:
深度学习是一种深度学习.组合学习组合学习甲状腺是什么?甲状腺是什么?转移学习转移学习

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