生成型人工智能对日本医生的实用性 面试培训:随机交叉试点研究
Takanobu Hirosawa1, Masashi Yokose1, Tetsu Sakamoto1
1Department of Diagnostic and Generalist Medicine, Dokkyo Medical University, 880 Kitakobayashi, Mibu-cho, Shimotsuga, 321-0293, Japan, 81 282861111.
在日本医学培训中,生成性AI对临床推理有很大的承诺,但传统方法在沟通技巧方面表现出色. 建议采用结合人工智能和面对面培训的混合方法,以获得最佳结果.
科学领域:
- 医学教育 医学教育
- 人工智能的人工智能
- 临床技能培训 临床技能培训
背景情况:
- 生成型人工智能 (AI) 越来越多地被用于医学教育.
- 它在特定文化背景中的应用,如日本医疗面试培训等,尚未得到充分探索.
- 这项研究调查了生成人工智能在日本培训医生的实用性.
研究的目的:
- 评估生成性AI作为医学面试培训工具.
- 将基于人工智能的培训与传统的面对面培训方法进行比较.
- 评估AI在日本医疗环境中的有效性.
主要方法:
- 一项随机交叉试点研究,涉及20名医生.
- 基于人工智能 (GPT平台) 和传统 (模拟患者) 面试站的比较.
- 在日语中使用6个指标进行评估,包括临床推理和沟通.
主要成果:
- 基于AI的站点在患者护理和沟通方面得分较低 (P=.009).
- 基于AI的站点在临床推理方面表现相似 (P=.10).
- 传统方法在面试的人际关系方面表现优于人工智能.
结论:
- 生成性人工智能显示出作为临床推理实践的补充工具的潜力.
- 人工智能可以实现自主学习,比传统方法有优势.
- 在日本,综合人工智能和传统方法的混合培训模型被推用于全面的医疗面试培训.
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