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A Novel Application of Musculoskeletal Ultrasound Imaging

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Published on: September 17, 2013

使用ChatGPT-4将肌肉骨放射学报告翻译成患者友好的摘要

Ian J Kuckelman¹, Karla Wetley², Paul Hyunsoo Yi³

¹University of Wisconsin School of Medicine & Public Health, 750 Highland Ave, Madison, WI, 53705, USA. kuckelman@wisc.edu.

Skeletal radiology

|January 25, 2024

概括

像ChatGPT-4这样的大型语言模型 (LLM) 可以为肌肉骨放射学报告生成准确的患者摘要. 这种人工智能工具有望改善患者对医学成像结果的理解.

科学领域:

放射学放射学是指放射学
人工智能的人工智能
医疗信息学医疗信息学

背景情况:

肌肉骨放射学报告通常包含复杂的医学术语.
患者可能很难理解他们成像报告的发现.
对放射学发现的明确沟通对于患者护理至关重要.

研究的目的:

评估使用ChatGPT-4来创建肌肉骨放射学报告的非专业人士摘要的可行性.
评估人工智能生成的摘要的准确性和完整性.
确定生成性人工智能是否可以自动制作患者友好的放射学报告.

主要方法:

六十份肌肉骨放射学报告 (肩膀,膝盖,腰椎MRI) 已被取消识别.
报告由ChatGPT-4处理,并提供特定的可读性和长度指令.
三位独立的读者评估了人工智能生成的摘要的准确性和完整性.

主要成果:

所有60个人工智能生成的摘要都符合字数和可读性标准.
在所有三种阅读器中,平均准确度评分都很高 (在3分级上从2.58到2.77不等).
平均完整性评分也很高 (从2.73到2.87不等).

结论:

聊天GPT-4在生成肌肉骨放射学报告的非专业人士摘要方面表现出高准确性和完整性.
一小部分摘要可能令人困惑或不准确.
生成型人工智能具有显著的潜力,可以自动化对MRI成像发现的患者友好的摘要.

关键词:

人工智能的人工智能是人工智能.聊天GPT 聊天在GPT 聊天大型语言模型.肌肉骨系统的疾病患者教育患者教育报告报告报告

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