基于机器学习的语音识别系统用于护理文档 - 一项试点研究
Tso-Ying Lee1, Chin-Ching Li2, Kuei-Ru Chou3
1Director of Nursing Research Center, Nursing Department, Taipei Medical University Hospital, Taipei, Taiwan; Associate Professor, School of Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan.
International journal of medical informatics
|September 10, 2023
概括
一个基于机器学习的语音识别系统在减少护理文档工作量方面表现有前途. 该系统在四次会议中获得了更高的准确性,这表明在临床记录管理中提高效率的潜力.
科学领域:
- 临床信息学 临床信息学
- 医疗保健中的人工智能
- 护理技术的护理技术
背景情况:
- 护理文档是工作负载的重要贡献者.
- 有效的记录保存对于有效的患者护理和医院运营至关重要.
- 现有的记录方法对护理人员来说可能是耗时的.
研究的目的:
- 评估基于机器学习的语音识别 (SR) 系统的有效性.
- 评估该系统对减少护士打字记录的临床工作量的影响.
- 在现实世界精神病房设置中测试SR系统.
主要方法:
- 基于深度学习的SR引擎使用医院护理数据进行训练.
- 21名护士与传统键盘输入一起评估了SR系统.
- 记录时间和识别错误率在四个会议中进行了比较.
主要成果:
- 该SR系统处理了超过3万个单词,准确度越来越高.
- 平均准确度从第一个会话中的87.06%提高到第四个会话中的95.07%.
- 该系统的平均处理速度为每秒0.928个单词.
结论:
- 基于机器学习的SR系统显示了可接受的准确性和减轻护士文档负担的潜力.
- 需要持续改进以解决SR转录错误.
- 需要进一步的研究,以使SR在跨专业的护理数字记录中得到最佳整合.
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