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在博士护理研究课程的学生中提高创造性人工智能能力
Meghan Reading Turchioe1, Sergey Kisselev1, Liesbet Van Bulck2
1Columbia University School of Nursing, New York, New York, United States.
Applied clinical informatics
|July 25, 2024
概括
博士护理学生在短暂的教育干预后改善了他们对医疗保健中生成人工智能 (AI) 应用的理解. 这项培训有助于护士在实践和研究中评估和安全使用人工智能工具.
科学领域:
- 护理教育 护理教育
- 医疗保健中的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 生成型人工智能 (AI) 工具已准备好整合到医疗保健实践和研究中.
- 处于领导角色的护士需要对AI安全有效实施的指导.
- 博士学位准备的护士在评估人工智能采用方面发挥着关键作用.
研究的目的:
- 开发和评估一个简短的教育干预.
- 加强博士生护理学生对医疗保健中适当的生成人工智能应用的知识.
- 为未来的护理领导人准备人工智能集成.
主要方法:
- 一个简短的干预被设计为护理博士学位数据科学课程.
- 教学讲座和实验室活动引入了生成性AI (ChatGPT 4.0).
- 学生在三个医疗保健用例中评估了ChatGPT的安全性和可用性.
主要成果:
- 学生们确定了ChatGPT在医疗保健任务中的优点和局限性.
- 参与者报告说,在使用生成AI方面,自我评价能力有所提高.
- 学生们对未来在工作中使用人工智能形成了意见.
结论:
- 教育干预有效地提高了护理博士生对适当生成AI使用的理解.
- 这支持学生批判性地评估和利用AI工具的能力.
- 对人工智能的准备在护理研究和实践中得到加强.
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