Aci-bench:一种用于基准测试的新型环境临床智能数据集 自动访问笔记生成
Wen-Wai Yim1, Yujuan Fu2, Asma Ben Abacha3
1Microsoft, Health AI, Redmond, 98052, USA. yimwenwai@microsoft.com.
Scientific data
|September 6, 2023
概括
研究人员开发了ACI-BENCH,这是人工智能辅助的最大数据集,用于从医生与患者对话中生成临床笔记. 这一基准对于评估医疗保健中的生成模型至关重要,它解决了当前人工智能开发中的差距.
科学领域:
- 医疗保健中的人工智能
- 自然语言处理自然语言处理.
- 临床信息学 临床信息学
背景情况:
- 像GPT-4这样的生成人工智能模型在应用程序中显示出巨大的潜力.
- 医疗保健,特别是临床笔记生成,面临着耗时文件的挑战.
- 医生倦怠程度因创建电子医疗记录的艰巨任务而加剧.
研究的目的:
- 为了解决缺乏大型,伦理来源的数据集,用于对AI辅助临床笔记生成进行基准测试.
- 为了引入环境临床智能基准 (ACI-BENCH) 库.
- 评估当前最先进的生成模型在这个任务上的表现.
主要方法:
- 创建了ACI-BENCH集体,这是从临床接触中生成对话到笔记的最大数据集.
- 包括几个领先的生成AI模型的基准性能.
- 专注于克服患者保密的障碍,以实现伦理数据共享.
主要成果:
- 该ACI-BENCH集体代表了对这个特定的人工智能任务的数据集大小的重大进展.
- 基准结果为当前最先进的模型能力提供了基线.
- 该数据集有助于进一步研究模型的弱点和评估指标.
结论:
- ACI-BENCH库对于严格评估和推进AI在临床笔记生成方面至关重要.
- 这一数据集的可用性将加速为医生开发更有效的AI工具.
- 标准化的基准测试对于理解和改进医疗保健文档中的AI性能至关重要.
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