用Chat赋予放射科医生权力GPT-4o:对心脏病例中的大型语言模型和放射科医生的比较评估
Turay Cesur1, Yasin Celal Gunes2, Eren Camur3
1Department of Radiology, Mamak State Hospital, Ankara, Türkiye.
Journal of thoracic imaging
|October 6, 2025
概括
大型语言模型 (LLM) 在心脏放射学方面表现有前途,ChatGPT-4o显著提高了一般放射科医生的诊断准确性和差异诊断得分. 克劳德3 Opus在LLMs中表现优越.
科学领域:
- 医疗成像中的人工智能
- 放射学和诊断成像 放射学和诊断成像
- 心血管放射学 心血管放射学
背景情况:
- 在心脏放射学中,评估大型语言模型 (LLM) 和人类放射科医生的诊断能力至关重要.
- 评估人工智能辅助,特别是ChatGPT-4o对诊断性能的影响是研究的一个关键领域.
研究的目的:
- 为了比较诊断准确度和差异诊断能力12LLMs与人类放射科医生 (一个心脏,3一般) 在心脏放射学.
- 调查ChatGPT-4o辅助对一般放射科医生的表现的影响.
主要方法:
- 从胸部放射学学会网站上使用了80个"本月心脏病例"病例.
- 一名LLM和一名放射科医生接受了基于文本的病例信息;其他放射科医生以视觉方式审查病例,有或没有ChatGPT-4o的协助.
- 诊断准确性和差异诊断 (DDx) 评分使用各种测试 (χ2,克鲁斯卡尔-瓦利斯,威尔科克森,麦克内马尔,曼-惠特尼U) 进行统计分析.
主要成果:
- 无助心脏放射科医生的准确率为72.5%. 聊天GPT-4o显著提高了一般放射科医生的准确性 (例如,放射科医生I从53.8%提高到70.0%).
- 聊天GPT-4o显著提高了所有放射科医生的DDx分数. 放射科医生-I的辅助性能接近无助心脏放射科医生的水平.
- 在LLM中,Claude 3 Opus和Claude 3.5 Sonnet获得了最高的准确率 (81.3%). 克劳德3Opus在DDx得分方面领先,超过了所有模型和放射科医生.
结论:
- 聊天GPT-4o显示出作为诊断支持工具的潜力,提高一般放射科医生的心脏成像性能.
- 需要进一步的研究来确定AI工具 (如ChatGPT-4o) 在放射实践中的最佳临床整合.
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