放射学变得很聊天:聊天GPT传奇展开
Harpreet Grewal1, Gagandeep Dhillon2, Varun Monga3
1Radiology, Florida State University College of Medicine, Pensacola, USA.
Cureus
|July 10, 2023
概括
像GPT-4这样的大型语言模型 (LLM) 显示了放射学在报告生成和教育等任务中的潜力. 然而,通用或不准确的输出需要进一步的研究,以确保安全的临床整合.
科学领域:
- 医疗成像医学成像
- 人工智能在医学中的应用
- 放射学 信息学 信息学
背景情况:
- 人工智能 (AI) 在医疗保健中越来越多地被采用,特别是在放射学等数据密集型领域.
- 大型语言模型 (LLM),如GPT-4,是具有有限的医学文献的新兴工具.
- 放射学为LLM应用提供了独特的机会,因为它依赖于数据和成像.
研究的目的:
- 探索GPT-4在放射学领域的潜在应用.
- 分析GPT-4输出对放射科医生在日常工作流程,患者教育和研究中的实用性.
- 确定关于在临床实践中实施LLM的未来研究的局限性和领域.
主要方法:
- 提示GPT-4生成放射学报告和模板.
- 该模型用于增强临床决策和建议研究文章标题.
- 对答案的准确性,实用性和临床环境中的潜在错误进行了评估.
主要成果:
- GPT-4在生成报告,模板和标题方面显示出潜力,有助于沟通和教育.
- 然而,回答有时是通用的,并包含事实上的不准确性,造成潜在的风险.
- 分析强调,需要仔细审查放射学LLM产生的内容.
结论:
- GPT-4为放射学提供了有前途的途径,包括工作流效率和教育支持.
- 法律法律管理的新性需要谨慎的实施,解决准确性和安全性的问题.
- 为了在放射学中负责任地整合LLMs,进一步的研究和准则的开发是必不可少的.
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