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乳腺癌中的人工智能:诊断,预后和治疗中的临床应用

Janhvi Singh¹, Omar Awad Alsaidan², Alhussain Aodah³

¹Thelansis Knowledge Partners, Gurugram, India.

Future oncology (London, England)

|December 24, 2025

概括

人工智能 (AI) 正在通过医学图像分析改善早期检测,诊断和预后,从而彻底改变乳腺癌 (BC) 护理. 这篇评论强调了人工智能.

科学领域:

在瘤学瘤学.
放射学放射学是一门学科.
医疗成像医学成像
人工智能的人工智能

背景情况:

乳腺癌 (BC) 是一个重要的全球健康问题,死亡率和发病率不断上升.
早期查和准确的诊断对于改善BC患者的治疗结果至关重要.
放射成像 (DBT,DM,MRI,超声波) 和组织病理学是BC评估的关键.

研究的目的:

审查人工智能 (AI) 应用在乳腺癌 (BC) 检测,诊断和预后方面的最新进展.
探索AI在图像分析,生物特征和结果预测中的作用.
确定AI在临床BC环境中实施AI的挑战和未来方向.

主要方法:

在PubMed数据库上进行文献搜索,搜索2018年至2025年间发表的研究.
专注于人工智能应用,包括病变检测,细分,诊断,图像增强和生物特征.
包括人工智能的使用与预测临床结果的multiomics数据.

主要成果:

人工智能在乳腺病变的快速检测,细分和诊断方面显示出显著的前景.
人工智能在BC中有助于通过数据增强进行亚型,分期和增强成像质量.
人工智能与多组学数据相结合,显示出预测生存,治疗反应和转移的潜力.

结论:

人工智能技术为乳腺癌的定量医学图像分析提供了强大的工具.
人工智能应用范围从图像解释到预测患者的结果和了解BC生物学.
对BC的AI的关键挑战包括数据组织,模型解释性和监管合规性.

关键词:

人工智能的人工智能是人工智能.乳腺癌:诊断的诊断方法临床应用临床应用机器学习是机器学习.预后预后预后治疗治疗治疗治疗治疗治疗

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