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相关概念视频

The Thyroid Gland01:23

The Thyroid Gland

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The thyroid gland is a small, butterfly-shaped gland located in the neck and covers the anterior surface of the trachea. The gland has two lateral lobes connected by a thin tissue mass called the isthmus. Internally, each lobe comprises many small spherical structures known as thyroid follicles, surrounded by a network of blood vessels.
The follicles have a central cavity lined by simple cuboidal to squamous epithelial cells called follicular cells. These cells produce the glycoprotein...
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Synthesis and Regulation of Thyroid Hormones01:20

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Low blood levels of the thyroid hormones — triiodothyronine (T3) and thyroxine (T4) — signal the hypothalamus to release the thyrotropin-releasing hormone (TRH). TRH then reaches the pituitary gland and stimulates the release of thyroid-stimulating hormone(TSH) into the bloodstream.
Upon reaching the thyroid gland, TSH stimulates the follicular cells' active uptake of iodide ions from the blood. The ions diffuse to the apical surface of the cells and are oxidized to iodine. The...
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相关实验视频

Updated: Jan 15, 2026

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甲状腺结节的细胞学分类诊断通过多式模式深度学习.

Yuanzheng Lou1,2,3,4, Yongjian Su4,5,6, Haoda Lu7

  • 1Department of Pathology, Nanfang Hospital and School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|October 16, 2025
PubMed
概括

一个人工智能平台,AI-TFNA,提高了甲状腺结节诊断的准确性和效率. 这种人工智能工具提高了诊断精度,解决了细胞病理学中的过度诊断和过度治疗问题.

关键词:
人工智能的人工智能是人工智能.细胞病理学诊断 细胞病理学诊断精细针吸入细胞学 (FNAC) 的研究.甲状腺结节的发生.整个幻灯片图像 (WSI) 是一个全幻灯片图像.

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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:

  • 甲状腺结节的患病率上升使细胞病理学资源受到压力,导致过度诊断和过度治疗.
  • 现有的诊断方法在甲状腺细针吸收 (TFNA) 的准确性和效率方面面临挑战.

研究的目的:

  • 开发和验证人工智能平台AI-TFNA,用于增强甲状腺结节诊断.
  • 为了提高诊断准确性,临床效率和在各种医疗保健环境中的通用性.

主要方法:

  • 在中国三家医院的4421个TFNA样本上训练了AI-TFNA,来自七个医疗中心的数据 (共20803个样本).
  • 使用内部和外部队列 (2,153个样本) 验证了AI-TFNA性能.
  • 集成的BRAF突变数据和图像外观迁移 (IAM) 为多式模式.

主要成果:

  • 内部验证显示高精度 (TBS I: 93.27%),灵敏度 (TBS V: 85.37%,TBS VI: 83.78%) 和特异性 (TBS II: 97.13%).
  • 外部验证证实了强大的通用性.
  • IAM提高了AI-TFNA灵敏度1.90%,特异性提高了8.12%.

结论:

  • AI-TFNA为甲状腺结节诊断提供快速,可靠的决策支持.
  • 人工智能平台显示出强大的潜力,可以推进甲状腺结节的诊断,减少过度治疗,并改善患者的治疗结果.