在紧急医疗环境中评估自动语音识别技术的有效性:对四个人工智能驱动的引擎进行比较研究
Research square
|August 26, 2024
概括
自动语音识别 (ASR) 显示出临床文档的希望,但在杂的紧急医疗服务 (EMS) 设置中扎. 目前的ASR技术需要显著改进,以便在医院前护理中准确地转录关键医疗信息.
科学领域:
- 医疗信息学 医疗信息学
- 语音技术 语言技术
- 紧急医疗服务 紧急医疗服务
背景情况:
- 自动语音识别 (ASR) 提供了实时临床文档的潜力,减轻了临床医生的负担.
- 在像EMS这样的喧,动态的医院前环境中,ASR的验证是不够的.
- 当前的ASR技术在具有挑战性的环境中准确地转录医疗对话方面存在局限性.
研究的目的:
- 探索ASR在EMS中的临床文档的局限性和未来潜力.
- 在模拟的EMS环境中评估领先的ASR发动机的性能.
主要方法:
- 评估了四个ASR引擎:谷歌语音到文本临床对话,OpenAI,亚马逊转录医学和Azure.
- 评估使用了40个模拟EMS记录.
- 对23个电子健康记录 (EHR) 类别进行了转录准确性的评估,分析了常见的错误类型.
主要成果:
- 谷歌语音到文本临床对话在评估的引擎中表现最好.
- 对于"精神状态"和"过敏"等类别,人们注意到了很高的准确性.
- 所有ASR发动机在"治疗"和"药物"等关键类别的性能都很低.
结论:
- 目前的ASR解决方案不足以在EMS中完全自动化临床文档.
- 进一步的进步对于在时间关键,动态的医疗环境中提高ASR准确性至关重要.
相关概念视频
01:30Assessment of Airway, Skin Color, and Use of Accessory Muscles
983
A thorough assessment of respiratory health is paramount in clinical settings to identify and manage respiratory distress and ensure adequate oxygenation. This article elaborates on the critical aspects of respiratory evaluation, including airway assessment, skin color examination, and the observation of accessory muscle use, which are integral to effectively diagnosing and managing patients with respiratory conditions.
Introduction
The initial evaluation of a patient's respiratory system...
Introduction
The initial evaluation of a patient's respiratory system...
983
01:29Issues And Trends In Healthcare Delivery System
5.6K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.6K