医疗成像教育中的人工智能:关于本科课程开发的建议
E Crotty1, A Singh1, N Neligan1
1Queensland University of Technology, School of Clinical Sciences, Faculty of Health, Brisbane, QLD, Australia.
Radiography (London, England : 1995)
|October 25, 2024
概括
人工智能 (AI) 教育对放射学学生至关重要. 这篇论文建议将AI模块集成到本科医学成像课程中,以为未来的放射科医生准备不断发展的技术,并确保患者的安全.
科学领域:
- 医疗成像医学成像
- 放射学 教育 放射学教育
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 越来越多地用于医学成像.
- 越来越需要在本科放射学课程中加强人工智能教育.
研究的目的:
- 为修订和重新调整本科医学成像课程提供建议.
- 引导课程提供者将人工智能教育纳入大学课程.
主要方法:
- 文献综述 文献综述 文献综述
- 实践者的洞察力 实践者的洞察力
- 产业前景 产业前景
- 为人工智能集成开发一个模块化框架.
- 关于纵向课程嵌入与实践经验的建议
主要成果:
- 建议在大学课程中整合人工智能的模块化框架.
- 课程模块包括数据科学,机器学习,AI伦理,治理,评估和临床应用.
- 建议使用实践经验和真实的评估进行纵向嵌入.
结论:
- 将人工智能教育整合到本科医学成像课程中,对于未来的放射科医生来说至关重要.
- 一个战略性的,多学科的方法确保学生获得全面的AI知识和批判性评估技能.
- 实际实施为放射科医生准备在患者护理中有效和安全地使用AI.
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