与教师指导的ChatGPT-4o在超声波培训中表现优于人工智能和传统学习:一个随机试验
Dao-Rong Hong1, Chun-Yan Huang2, Jiu Gao2
1Department of Ultrasonography, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.
Frontiers in digital health
|March 11, 2026
概括
结合人工智能 (ChatGPT-4o) 和教师指导的混合学习方法与仅使用人工智能或传统方法相比,显著改善了超声波住院人员的表现. 仅人工智能在解释静态超声波图像方面就存在局限性.
科学领域:
- 医学教育 医学教育
- 人工智能在医学中的应用
- 诊断成像 诊断成像 诊断成像
背景情况:
- 超声波培训由于其依赖操作者的性质和图像解释的复杂性而带来挑战.
- 像ChatGPT-4o这样的多式大型语言模型 (LLM) 提供了高效的知识检索,但在分析静态超声波图像方面存在局限性.
- 制定有效的培训策略对于住院人员对超声波的熟练程度至关重要.
研究的目的:
- 评估不同培训模式对超声波住院医生的有效性.
- 为了比较传统的学习,AI-only培训 (ChatGPT-4o) 和混合方法 (AI加教师指导).
- 评估人工智能集成对超声波中居民表现的影响.
主要方法:
- 一个前性的,单中心随机对照试验,涉及45名第一年超声波住院医生.
- 居民被分配到控制 (传统资源),仅使用人工智能 (ChatGPT-4o) 或混合 (ChatGPT-4o + 教师辅导) 组.
- 经过3周的干预,随后进行了150项检查,评估纯文本和基于图像的知识.
主要成果:
- 与AI单独 (119.87 ± 19.11) 和对照 (110.60 ± 20.45) 组 (P=0.02) 相比,混合组获得了明显更高的整体得分 (128.40 ± 18.25).
- 在混合组中,在纯文本问题 (P=0.03) 和特定领域如产科/妇科 (P=0.04) 和表面器官超声波 (P=0.047) 中观察到更好的表现.
- 聊天GPT-4o在基于文本的问题上显示了85%的准确性,但在基于图像的问题上只有47%,突出显示了AI在视觉解释方面的局限性.
结论:
- 与人工智能或传统方法相比,由教师指导的AI集成策略可以提高短期超声波住院人员的表现.
- 该研究表明,虽然人工智能可以补充学习,但其在静态超声波图像解释方面的有效性仍然有限.
- 结合人工智能与专家教师指导的混合学习方法似乎对超声波教育最有益.
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