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使用ChatGPT提高患者对外围的MRI发现的理解:一个随机的单中心研究

Easan Anand^1,2, Itai Ghersin¹, Gita Lingam^1,2

¹Robin Phillips' Fistula Research Unit, St Mark's The National Bowel Hospital, London NW10 7NS, UK.

Diagnostics (Basel, Switzerland)

|January 10, 2026

概括

大型语言模型 (LLM) 可以创建复杂的MRI鱼报告的患者友好的摘要,提高理解. 然而,由于人工智能产生的内容可能存在不准确性和幻觉,需要仔细监督.

科学领域:

医学成像信息学医疗成像信息学
医疗保健中的人工智能
患者沟通患者沟通

背景情况:

复杂的磁共振成像 (MRI) 飞报告对患者的理解构成了挑战.
大型语言模型 (LLM) 显示了将技术医疗信息转化为可访问的摘要的潜力.

研究的目的:

评估GPT-4o的临床实用性,安全性和患者接受度,以生成对患者友好的MRI鱼报告摘要.
为了比较AI生成的摘要与原始MRI报告的可读性,可信性,有用性和理解性.

主要方法:

这是一项三阶段研究,涉及快速工程,由多学科小组对AI输出进行审查,并对原始和人工智能生成的摘要进行患者评估.
第二阶段评估了250份MRI鱼报告的幻觉和主题内容.
第三阶段随机选择了61名患者,将AI摘要与可读性,信任度,有用性和理解度的原始报告进行比较.

主要成果:

人工智能生成的摘要在可读性,理解性和有用性方面明显优于原始报告 (p < 0.001).
幻觉发生在11%的AI输出中;临床医生指出,尽管语言得到了改进,但存在不准确的风险.
人工智能总结的Flesch-Kincaid得分更高 (66比26),表明理解更容易.

结论:

临床医学可以提高患者对复杂的MRI报告的理解,但需要有结构的监督来减轻幻觉和不一致的术语等风险.
安全的实施需要特定领域的改进,临床医生验证和标准化的报告模板与简要摘要.
未来的人工智能开发应该专注于临床医生批准的标准化模板,以加强患者沟通.

关键词:

克罗恩氏病是什么克罗恩氏病是什么人工智能的人工智能是人工智能.密码腺状囊密码腺状囊大型语言模型.磁共振成像技术的使用患者沟通患者沟通周围上的.

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