打破障碍:人工智能对资源稀缺的医疗系统中的病理学和瘤学的影响
Alon Vigdorovits1,2, Maria Magdalena Köteles3, Gheorghe-Emilian Olteanu2,4,5
1Department of Pathology, County Clinical Emergency Hospital, Faculty of Medicine and Pharmacy, University of Oradea, 1 December Sq. No. 10, 410087 Oradea, Romania.
Cancers
|December 9, 2023
概括
病理学中的人工智能 (AI) 可以通过提高诊断准确性和预测治疗结果来增强癌症护理. 本综述探讨了瘤学,临床工具和数字病理学采用的挑战中的AI应用.
科学领域:
- 在瘤学瘤学.
- 数字病理学数字病理学
- 人工智能的人工智能
背景情况:
- 病理学对于癌症诊断,治疗反应预测和生存分析至关重要.
- 在资源有限的环境中,病理学资金往往不足.
- 数字病理学可以实现人工智能集成,以提高效率和数据提取.
研究的目的:
- 审查AI在瘤病理学中的应用.
- 讨论已经获得临床批准的AI工具.
- 确定在数字病理学中采用人工智能的挑战和解决方案.
主要方法:
- 人工智能在瘤病理学方面的文献综述.
- 对人工智能研究方向的分析:瘤分类,分子变异预测,生物标志物量化.
- 检查临床批准的AI工具和监管途径.
- 讨论数字病理学和人工智能实施的障碍.
主要成果:
- 人工智能研究侧重于瘤分类,分子预测和生物标志物量化.
- 几种人工智能驱动的病理学工具已经获得了临床使用的监管批准.
- 数字病理基础设施和人工智能集成仍然存在重大障碍.
结论:
- 人工智能通过先进的病理学为癌症治疗提供了变革性的潜力.
- 克服实施挑战是实现AI在病理学方面的好处的关键.
- 需要持续的研究和投资,才能将人工智能完全整合到临床病理学工作流程中.
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