相关实验视频

Updated: Sep 15, 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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一个统一的本体学和可解释的框架来解码来自新闻数据的AI风险

Chuan Chen1, Peng Luo2,3, Huilin Zhao4

  • 1Chair of Cartography and Visual Analytics, Technical University of Munich, Munich, Germany.

Scientific reports
|July 15, 2025
PubMed
概括

本研究引入了一个统一的本体模型,以全面地绘制人工智能 (AI) 风险,从广泛的类别到特定事件. 它使用视觉分析和机器学习来分析AI风险数据,提供对驱动因素的新见解.

关键词:
人工智能伦理学人工智能风险AI风险可解释的机器学习新闻数据新闻数据存在论模型是存在论模型.

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