人工智能和默认知识在助产医院的整合:改善医疗保健结果的政策影响
Shoko Takeuchi1, Kazumi Kubota2,3,4, Sachiyo Nakamura1
1Department of Nursing, Graduate School of Medicine, Yokohama City University, Yokohama, Kanagawa, Japan.
人工智能 (AI) 可以捕捉默契的助产知识,以改善孕产妇的护理. 这项技术使经验智慧正式化,增强基于证据的实践和政策,尽管道德考虑至关重要.
科学领域:
- 探索人工智能 (AI) 在医疗保健中的应用.
- 专注于机器学习 (ML) 和自然语言处理 (NLP) 以获取知识.
背景情况:
- 助产士的护理在很大程度上依赖于默许的,经验性的知识,而这些知识在政策中经常被忽视.
- 人工智能为正式化这些知识提供了一条途径,改善结果和政策认可.
研究的目的:
- 调查人工智能在捕获隐性助产知识中的作用.
- 评估AI在提高助产士实践和政策方面的潜力.
- 检查人工智能如何促进将体验知识整合到基于证据的实践中.
主要方法:
- 从2015-2025年对同行评审文献进行系统审查.
- 包括关于人工智能在医疗保健,助产士和人工智能伦理方面的研究.
- 专注于AI在临床环境和助产士教育中的应用.
主要成果:
- 人工智能可以释放隐秘的助产知识,特别是在围外伤预防和临床决策方面.
- 人工智能模型提供实时风险评估,减少临床变异性.
- 从经验丰富的助产士获得的定性数据的分析是关键.
结论:
- 人工智能通过正式化默认知识和改进决策来推动助产的巨大潜力.
- 解决道德问题,数据隐私和算法偏见对于人工智能集成至关重要.
- 政策框架必须支持助产士的人工智能开发,并为从业人员提供必要的培训.
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