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聊天GPT-4视觉:一个有前途的工具来诊断甲状腺结节

Dao-Rong Hong¹, Chun-Yan Huang², Huo-Hu Zhong¹

¹Department of Ultrasonography, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.

Frontiers in medicine

|August 14, 2025

概括

聊天GPT-4视觉显示在分析甲状腺结节方面有前途,与住院医生的诊断准确度相匹配. 这种人工智能工具为风险分层提供了一种标准化的方法,有可能改善甲状腺癌的检测.

科学领域:

医疗成像中的人工智能
诊断性的超声波检查
甲状腺结节分析

背景情况:

甲状腺结节很常见,需要对恶性瘤进行准确的风险分层.
目前的超声波分析依赖于经验丰富的超声波仪和已建立的指导方针,如C-TIRADS.
人工智能工具为标准化和一致的图像解释提供了潜力.

研究的目的:

评估ChatGPT-4视觉在分析甲状腺结节的超声波图像中的诊断效果和一致性.
为了比较ChatGPT-4 Vision与不同经验水平的超声波仪的性能.

主要方法:

一项前性研究,涉及124名患有病理确认甲状腺结节的患者.
超声波图像由ChatGPT-4 Vision和两个超声波仪使用C-TIRADS指南进行分析.
性能与细针吸收 (FNA) 活检或外科病理学结果进行了比较.

主要成果:

聊天GPT-4视觉实现了86.2%的灵敏度和60.0%的特异性 (AUC 0.731),相当于住院医生,但低于主治医生.
人工智能与居民分类有很好的一致性 (Kappa=0.729),但与主治医生相比,与病理诊断的一致性较低 (Kappa=0.457对比0.816).

结论:

聊天GPT-4视觉显示甲状腺结节风险分层的临床实用性,性能与住院医生相比.
人工智能的标准化能力与精密医学保持一致,并可能支持未来与先进超声波技术的整合.

关键词:

聊天GPT 聊天在GPT 聊天诊断诊断诊断诊断诊断诊断病理学的病理学甲状腺结节的发生.超声波超声波是指超声波的使用.

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