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Updated: May 12, 2026

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短暂的学习和可解释的AI用于结肠癌组织病理学:具有多技术可解释性的原型网络

Asma Merabet1, Asma Saighi1, Zakaria Laboudi2

  • 1Artificial Intelligence and Autonomous Things Laboratory (LAIOA), University of Oum El Bouaghi, Oum El Bouaghi, 04000, Algeria; Department of Mathematics and Computer Sciences, University of Oum El Bouaghi, Oum El Bouaghi, 04000, Algeria.

International journal of medical informatics
|November 13, 2025
PubMed
概括

这项研究引入了一个数据高效的框架,用于结肠癌诊断,使用少量射击学习和可解释的AI. 该模型以最小的数据实现了高精度,提供可解释的视觉输出,用于可靠的诊断.

关键词:
结肠癌的组织病理学ConvNeXt-tiny 的意思是什么意思可解释的人工智能 (XAI)有几次射击学习学习.这是Grad-CAM.在 LIME 时代,一个典型的网络原型.t-SNE可视化的可视化

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相关概念视频

Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...