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基于临床超声波特征的可解释机器学习模型的诊断价值,用于卵泡甲状腺癌的卵泡甲状腺癌

Yuxin Zheng1,2,3, Yajiao Zhang1,2,3, Kefeng Lu4

  • 1Second Clinical College, Zhejiang University of Traditional Chinese Medicine, Hangzhou, China.

Quantitative imaging in medicine and surgery
|September 16, 2024
PubMed
概括

这项研究开发了一种有效的XGBoost机器学习模型,使用超声波功能准确诊断卵泡甲状腺癌 (FTC),改善患者的预后和治疗. 该模型在验证中实现了高诊断准确性,有助于个性化患者护理.

关键词:
卵泡性甲状腺癌 (FTC) 是一种沙普利添加式扩展法 (SHAP)机器学习 (ML) 是指机器学习.超声波诊断诊断 超声波诊断 超声波诊断

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