医学
甲状腺癌
软件
间隙
甲状腺
医学物理学
甲状腺结节
放射科
模式
颈淋巴结
人工智能
计算机科学
病理
过程(计算)
活检
人工智能应用
小贩
癌症
联营
主题
淋巴
工作流程
作者
Johnson Thomas,Franklin N. Tessler
出处
期刊:Thyroid
[Mary Ann Liebert, Inc.]
日期:2026-01-07
卷期号:36 (2): 133-140
标识
DOI:10.1177/10507256251412316
摘要
BACKGROUND: In this updated review, we will discuss the role of artificial intelligence (AI) in the assessment of thyroid nodules, cervical lymph nodes, and cytology or histology specimens, followed by guidance for practices wishing to install AI systems. SUMMARY: To date, six AI platforms for assessing sonograms of thyroid nodules have been cleared by the United States Food and Drug Administration, with generally good performance, especially when compared with that of less-experienced physicians. Multimodality large language models have also been tested in this context, but with less impressive results so far. Software to evaluate lymph nodes and biopsy or surgical specimens shows promise, though no systems have yet reached the marketplace. The process of evaluating and installing an AI system in a practice requires consideration in five areas: information technology, vendor support, effectiveness, usability, and finance. Engagement of people with subject matter expertise in all these domains is recommended, beginning with product selection. CONCLUSIONS: AI tools for the evaluation of thyroid nodules continue to proliferate, and commercial software to assess lymph nodes and slide specimens may soon become available. Attention to detail is critical for successful implementation and operation.
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