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用于诊断和治疗甲状腺癌的深度学习:一篇评论

Rili Gao¹, Shangqing Mai², Song Wang²

¹Department of Endocrinology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.

Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists

|August 1, 2025

概括

深度学习 (DL) 显著推进了甲状腺癌的诊断和治疗,提高了图像分析和预后等领域的准确性. 克服采用障碍是实现DLL的关键.

科学领域:

在瘤学瘤学.
医疗成像医学成像
人工智能的人工智能

背景情况:

在甲状腺疾病研究中的深度学习 (DL) 应用迅速扩大.
在甲状腺癌研究中,DL正在推动重大创新.

研究的目的:

审查最近在甲状腺癌诊断和治疗中DL应用的进展.
为临床医生提供关于甲状腺癌护理中的DL的最新信息.

主要方法:

系统审查过去五年发表的研究.
在PubMed数据库中搜索了甲状腺癌诊断,治疗和预后中的DL应用.

主要成果:

像CNN,LSTM和GAN这样的DL模型在超声波图像分析,病理图像分类和甲状腺外延伸评估方面表现突破性.
在个性化治疗规划和预后预测方面,DL显示出前景.
临床采用受到技术,临床和伦理挑战的阻碍.

结论:

DL技术正在提高甲状腺癌的精确诊断和治疗.
DL有可能提高患者的诊断准确性和治疗结果.

关键词:

卷积神经网络是一种卷积神经网络.深度学习是一种深度学习.精准医学是一门精准医学.甲状腺癌是一种癌症.甲状腺超声波甲状腺超声波

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