起草未来:人工智能的黎明 在放射学中报告生成
Jarrel C Y Seah1,2,3, Jennifer S N Tang3,4, Aengus Tran3
1Division of Neuroradiology, Massachusetts General Hospital, Boston, Mass.
Radiology
|July 29, 2025
概括
人工智能 (AI) 通过自动化报告生成,为全球放射科医生短缺提供解决方案. 综合人工智能和大型语言模型 (LLM) 可以创建放射学报告草案,提高效率和可扩展性.
科学领域:
- 医学成像和人工智能 医学成像和人工智能
- 放射学工作流的优化 工作流的优化
- 临床决策支持系统 临床决策支持系统
背景情况:
- 全球放射科医生短缺导致诊断延迟和临床医生疲劳.
- 放射学工作量不断增加,需要创新的解决方案来提高效率.
- 人工智能 (AI) 正在探索解决这些挑战.
研究的目的:
- 探索全面的人工智能和大型语言模型 (LLM) 在自动化放射学报告生成方面的潜力.
- 讨论将人工智能驱动的报告工具集成到临床工作流程中的问题.
- 想象人工智能在常规放射学实践中的未来.
主要方法:
- 开发全面的AI算法,训练有素的多任务学习,用于图像分析.
- 利用大型语言模型 (LLM),包括多式联络LLM,用于文本和图像输入.
- 专注于从医疗图像中生成准确,类似人类的草稿报告.
主要成果:
- 综合人工智能可以对放射和CT图像进行分类和检测多种异常.
- 多模式LLM可以从医学图像直接生成放射学报告草案.
- 人工智能产生的报告显示,有潜力显著提高效率和扩大劳动力能力.
结论:
- 人工智能,特别是通过全面的人工智能和多式联络LLM,为放射科医生短缺提供了可行的解决方案.
- 自动报告生成可以大大提高高容量放射学设置的效率.
- 人工智能报告工具安全有效的临床整合框架对于未来的采用至关重要.
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