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相关实验视频

Updated: Sep 11, 2025

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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病理学中的人工智能:推进可扩展应用的大型模型.

Zhiping Xiao1, Bin Feng2, Junwei Yang2

  • 1Department of Computer Science and Engineering, University of Washington, Seattle, Washington, USA; email: patxiao@uw.edu, swang@cs.washington.edu.

Annual review of biomedical data science
|August 11, 2025
PubMed
概括

人工智能 (AI) 正在改变医学研究,特别是在病理学领域. 本综述强调了人工智能数据集和模型,为大规模应用铺平了道路,同时注意到了伦理方面的考虑.

关键词:
人工智能的人工智能是人工智能.深度学习是一种深度学习.组合模型组合模型组合模型基础模型 基础模型机器学习是机器学习.医疗数据集是一个医疗数据集.病理学的病理学

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科学领域:

  • 医学研究 医学研究
  • 病理学 病理学 病理学
  • 人工智能的人工智能

背景情况:

  • 人工智能 (AI) 支持病理学研究的历史悠久.
  • 最近的进展包括病理学基础模型和病理学合奏模型的开发.
  • 这些大型模型是建立在该领域之前的人工智能创新的基础上.

研究的目的:

  • 审查与病理学相关的AI数据集和模型.
  • 探索大规模AI模型在病理学中的出现和影响.
  • 讨论人工智能在敏感医疗应用中的伦理含义.

主要方法:

  • 在病理学中对AI数据集和模型的文献综述.
  • 分析AI在病理学中的历史发展和当前趋势.
  • 讨论道德问题,包括隐私风险.

主要成果:

  • 人工智能显著增强了病理学研究,提供了新的研究可能性.
  • 大规模人工智能模型的开发是病理学的最新趋势.
  • 伦理考虑,如隐私,对于AI实施至关重要.

结论:

  • 包括大型模型在内的人工智能对于推进病理学研究至关重要.
  • 对可用的数据集和模型的全面理解对于未来的应用是必不可少的.
  • 将人工智能创新与伦理考虑相平衡,对于在医学中负责任实施至关重要.