相关实验视频

Updated: Jul 11, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

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对医疗成像中的人工智能方法的可解释性和可解释性的范围审查

Mélanie Champendal1, Henning Müller2, John O Prior3

  • 1School of Health Sciences HESAV, HES-SO, University of Applied Sciences Western Switzerland, Lausanne, CH, Switzerland; Faculty of Biology and Medicine, University of Lausanne, Lausanne, CH, Switzerland.

European journal of radiology
|November 17, 2023
PubMed
概括

医学成像中的可解释的人工智能 (XAI) 正在快速增长,重点是MRI,CT和肺部和大脑疾病的放射学. 标准化术语对于未来的XAI开发至关重要.

关键词:
计算机断层扫描 (CT) 是一种计算机断层扫描.深度学习 (Deep Learning) 是一种深度学习.可以解释的可解释性.机器学习 机器学习磁共振成像 (MRI) 是一种磁共振成像技术.医疗成像医学成像放射学 放射学 放射学 放射学透明度 透明度 透明度

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