现在是病理学全数字化方法的时候了:对当前的人工智能应用和未来方向进行系统审查
Giorgio Cazzaniga1, Mattia Rossi2, Albino Eccher3,4
1Department of Medicine and Surgery, Pathology, Fondazione IRCCS San Gerardo dei Tintori, Università di Milano-Bicocca, Monza, Italy. giorgio9cazzaniga@gmail.com.
Journal of nephrology
|September 28, 2023
概括
人工智能 (AI) 正在病理学领域取得进展,深度学习对复杂的脏活检分析显示出希望. 多学科合作是开发用于病诊断的有效AI工具的关键.
科学领域:
- 腎病理學 腎病理學
- 医疗人工智能 医疗人工智能
- 数字病理学数字病理学
背景情况:
- 人工智能 (AI) 在病理学中的整合正在迅速扩大,面临着各种组织学技术和数据共享需求等挑战.
- 本文审查了人工智能应用在分析病理方面的历史轨迹和未来潜力.
- 目前的研究主要集中在更简单的任务上,但正在向复杂的分析转移,例如多层分类.
结论:
- 深度学习技术显示出使用先进的染色方法进行全面脏活检评估的巨大潜力.
- 正在探索混合和协作学习方法,以有效利用未标记的数据.
- 临床相关的人工智能工具的开发需要脏病理学家,计算机科学家和临床医生之间的密切合作.
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