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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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人工智能在瘤成像查中的应用

Zhihong Guo1, Meng Xu, Chaoliang Zhong

  • 1Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Naval Medical University, Shanghai, China.

International journal of surgery (London, England)
|November 25, 2025
PubMed
概括
此摘要是机器生成的。

瘤成像中的人工智能 (AI) 增强了各种方式的早期癌症检测. 解决数据集偏差和监管需求等挑战对于在癌症护理中公平实施人工智能至关重要.

关键词:
人工智能的人工智能癌症查 癌症查临床应用 临床应用深度学习是一种深度学习.图像成像方式.

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科学领域:

  • 在瘤学瘤学.
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 全球癌症负担正在上升,需要改进早期检测方法.
  • 人工智能 (AI) 在癌症成像中为癌症查提供了变革性的潜力.
  • 目前的成像方法在早期和准确的癌症检测方面存在局限性.

研究的目的:

  • 审查AI在癌症成像中用于癌症检测的演变和临床应用.
  • 通过各种成像技术突出显示人工智能驱动的早期癌症查方面的进展.
  • 应对挑战,并提出解决方案,以有效地在医学成像中实施人工智能.

主要方法:

  • 对瘤成像中的AI应用进行全面的文献综述.
  • 分析AI在超声波,X射线,CT,MRI和癌症检测内镜中的作用.
  • 检查包括数据集偏差,监管框架和整合障碍在内的挑战.

主要成果:

  • 人工智能在多种成像方式的早期癌症检测方面取得了重大进展.
  • 确定的主要挑战包括数据偏差,监管障碍和技术整合.
  • 标准化的数据集,可解释的AI和公平的实施对于成功至关重要.

结论:

  • 人工智能将通过更早,更准确的检测和个性化的风险分层来彻底改变癌症护理.
  • 解决实施挑战对于实现人工智能的全部潜力来改善患者的治疗结果至关重要.
  • 将人工智能与临床验证和伦理治理相结合,将提高癌症查和治疗.