细胞癌的AI辅助诊断:基于世卫组织2022年分类的教育需求和认知评估
Yuxi He1, Xiaoxue Yin2, Xu Shi1
1Department of Urology, Institute of Urology, Sichuan Clinical Research Center for kidney and urologic diseases, West China Hospital, Sichuan University, No.37 Guoxue Alley, Wuhou District, Chengdu, Sichuan Province, 610041, China.
BMC medical education
|October 2, 2025
概括
医学专业的学生认识到人工智能.
科学领域:
- 医学教育 医学教育
- 人工智能在病理学中的应用
- 细胞癌的诊断 细胞癌的诊断
背景情况:
- 医学学生对人工智能辅助细胞癌 (RCC) 诊断和世卫组织2022年分类的理解至关重要.
- 现有的课程可能无法充分为学生准备在诊断中整合人工智能.
- 关于AI在病理学的认知偏见和教育需求需要进行调查.
研究的目的:
- 探索医学学生对人工智能辅助RCC诊断的看法,教育需求和认知偏见.
- 评估学生对人工智能工具的熟悉程度和对基于人工智能的病理学的信任.
- 评估对世卫组织2022年RCC分类的理解.
主要方法:
- 对249名医学学生进行横截面调查.
- 评估对人工智能工具的熟悉程度,对人工智能病理学的信任,以及对诊断标准的了解.
- 调查了世卫组织2022年分类和人工智能培训需求的认识.
主要成果:
- 大多数学生承认AI在诊断准确性方面的潜力,但对过度依赖和自动化偏见表示担忧.
- 有关世卫组织2022年分类存在重大知识差距,泌尿学学生表现出更高的认识.
- 近70%的参与者主张强制性人工智能培训,重点是临床验证.
结论:
- 需要将人工智能创新与强大的验证协议和更新的课程相结合.
- 解决技术限制,数据标准化和道德问题对于人工智能采用至关重要.
- 未来的研究应该将人工智能开发与教育改革和准确的RCC诊断的伦理框架相协调.
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