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Updated: Sep 20, 2025

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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乳腺病理学中的人工智能:概述和最近的更新

Sneha Datwani1, Hikmat Khan1, Muhammad Khalid Khan Niazi1

  • 1Department of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA.

Human pathology
|May 29, 2025
PubMed
概括

人工智能 (AI) 正通过改进诊断,分级和生物标志物量化来彻底改变乳腺病理学. 虽然挑战仍然存在,但人工智能集成有望提高乳腺癌管理的准确性和效率.

科学领域:

  • 病理学 病理学 病理学
  • 数字病理学数字病理学
  • 人工智能的人工智能

背景情况:

  • 乳腺癌诊断在很大程度上依赖于组织病理学,面临着工作量,变化和复杂性的挑战.
  • 数字病理学和全幻灯片成像 (WSI) 为人工智能集成铺平了道路.
  • 人工智能提供解决方案,以提高乳腺病理学的准确性和效率.

研究的目的:

  • 审查乳腺病理学AI应用的进展.
  • 探索AI在诊断,分级,转移检测和生物标志物量化中的作用.
  • 讨论新兴的人工智能应用和该领域的未来方向.

主要方法:

  • 关于人工智能在乳腺病理学中的当前文献的综述.
  • 对人工智能在诊断,分类,分级和生物标志物分析中的应用进行分析.
  • 讨论人工智能在预后,治疗反应和生物标志物发现方面的潜力.

主要成果:

  • 人工智能在诊断,分类,分级和生物标志物量化方面取得了显著进展 (ER,PR,HER2,Ki-67).
  • 新兴的人工智能角色包括预后预测,治疗反应评估和瘤微环境分析.
  • 人工智能采用的障碍包括数据质量,概括性,解释性和监管障碍.
关键词:
人工智能的人工智能是人工智能.乳腺癌是什么 乳腺癌是什么乳腺病理学的生物标志物预测 预后 预测 预测整个幻灯片成像成像系统.

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结论:

  • 人工智能正在改变乳腺病理学,提供更高的准确性和效率.
  • 解决数据质量和临床整合等挑战对于广泛采用人工智能至关重要.
  • 未来的研究应该专注于基础模型,多式联运数据,可解释的AI和现实世界的验证.