通过交互式实践研讨会教授数据科学,使用临床相关的案例研究
Alvin D Jeffery1, Patricia Sengstack2
1Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, United States.
Applied clinical informatics
|August 30, 2024
概括
这次研讨会成功地向300多名临床医生教授了机器学习等数据科学概念. 培训侧重于实际应用,增强他们使用数据提高医疗保健质量的能力.
科学领域:
- 医疗信息学 医疗信息学
- 数据科学教育数据科学教育
- 临床决策支持 临床决策支持
背景情况:
- 实践临床医生,特别是护士的数据科学教育存在差距.
- 对数据科学方法的有限接触阻碍了医疗保健提供者利用和批评这些工具的能力.
- 本案例报告详细介绍了一个创新的研讨会,旨在解决这一教育赤字.
研究的目的:
- 为临床医生提供基础数据科学知识.
- 让临床医生能够有效地为质量改进团队做出贡献.
- 提高对机器学习和临床应用预测建模的理解.
主要方法:
- 一个交互式研讨会,强调核心机器学习和预测建模概念.
- 使用Python笔记本使用临床案例研究 (败血症识别,阿片类药物过量) 的实践练习.
- 专注于与临床实践相关的实际应用和模型性能评估.
主要成果:
- 来自不同环境的300多名参与者提供了积极的反.
- 研讨会有效地使复杂的数据科学主题能够让临床医生接触到.
- 在吸引临床医生使用数据科学原则方面取得了成功.
结论:
- 研讨会的方法优先考虑吸引人的内容和实际应用,与成人学习原则保持一致.
- 为临床医生提供数据科学知识对于导航数据驱动的医疗保健领域至关重要.
- 该倡议为将数据科学教育纳入医疗保健信息学和专业发展提供了一个模板.
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