人工智能在从显微镜图像中识别组织组织的效率
Mustafa Saad Yousuf1, Bashar Issa Almaraziq2
1Department of Anatomy, Physiology, and Biochemistry, Faculty of Medicine, The Hashemite University, Zarqa, Jordan.
Anatomy & cell biology
|January 22, 2026
概括
谷歌Gemini和ChatGPT 4o显示出识别组织学图像的潜力,Gemini显示出卓越的准确性. 这种人工智能应用可以帮助组织学教育和实践,尽管批判性评估仍然是必不可少的.
科学领域:
- 组织病理学 组织病理学
- 医学教育 医学教育
- 人工智能在医学中的应用
背景情况:
- 组织学是一个至关重要的,但具有挑战性的医学学科.
- 人工智能 (AI) 提供先进的图像识别功能.
- 人工智能有很大的潜力来支持组织学研究.
研究的目的:
- 为了评估ChatGPT 4o和谷歌双子座2.0闪存的组织图像识别性能.
- 为了比较这些AI模型在识别各种组织样本时的准确性和一致性.
主要方法:
- 高分辨率的组织图像被呈现给两种AI模型.
- 任务包括识别基本组织类型,器官和特定结构.
- 通过评分来评估性能,并重复测试以进行一致性分析.
- 统计分析包括麦克纳马测试和卡帕系数.
主要成果:
- 这两种AI模型都表现出良好的图像识别,谷歌双子座的表现优于ChatGPT.
- 与ChatGPT (65%) 相比,Gemini获得了更高的正确识别分数 (75%-77.5%).
- 统计分析显示,模型之间存在显著差异,只有公平协议 (Kappa).
- 肌肉组织的识别是最容易的;上皮组织是最具挑战性的.
结论:
- 人工智能,特别是谷歌双子座,在协助组织学图像识别方面表现有前途.
- 人工智能工具可以对学生和组织学家有价值,增强学习和诊断支持.
- 用户必须运用批判性判断,因为在组织学分析中可能出现AI错误.
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