数据密集型研究范式:临床专业研究生教育中的挑战和应对
Chunhong Yang1, Yijing Chen2, Changshun Qian3
1Academic Affairs Office, First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
Frontiers in medicine
|February 24, 2025
概括
大数据和人工智能在医学中的整合需要临床研究生教育来适应. 这涉及课程改革,教师发展和更新评估,以培养未来的医疗保健专业人员在跨学科的医疗计算机技能.
科学领域:
- 医疗信息学 医疗信息学
- 健康 专业 教育 卫生 专业 教育
- 在医疗保健中的数据科学.
背景情况:
- 医疗领域越来越多地利用大数据,人工智能 (AI) 和机器学习 (ML).
- 这种转变需要数据密集型临床研究的新范式,推动医学进步.
- 临床专业的现有研究生教育面临着适应这种数据驱动的转型的挑战.
研究的目的:
- 确定数据密集型临床研究所带来的挑战,以获得医学研究生教育.
- 为临床研究生课程提出适应性策略.
- 确保培养未来的医疗保健专业人员,熟练掌握医疗计算机集成技术.
主要方法:
- 对人工智能和大数据对临床研究范式的影响分析.
- 识别当前研究生医学教育中的挑战.
- 对抗措施的建议,包括课程,教师,资源,评估和道德.
主要成果:
- 研究生医学教育需要显著的适应,以整合数据科学和AI.
- 关键的挑战包括多学科融合,教师短缺以及不断发展的学习/评估方法.
- 拟议的对策涉及课程改革,教师发展,资源共享和道德教育.
结论:
- 临床研究生教育必须不断发展,以满足数据密集型医学研究的需求.
- 发展数据分析和编程方面的跨学科技能对于未来的医疗保健专业人员至关重要.
- 实施拟议的战略将促进医疗计算机集成人才,促进医疗创新.
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