人工智能在非学术,非商业病理学实验室的实际实施:现实世界的经验和经验教训
Frederik Deman1,2, Glenn Broeckx1,3, Sabine Declercq1
1PA2, Department of Pathology, Ziekenhuis aan de Stroom (ZAS), Antwerp, Belgium.
Histopathology
|June 17, 2025
概括
人工智能 (AI) 在病理学中的整合改善了前列腺活检诊断,减少了免疫组织化学测试和周转时间. 学到的经验教训为未来在医疗保健环境中采用人工智能提供了指导.
科学领域:
- 数字病理学数字病理学
- 医学诊断 医学诊断 医学诊断
- 医疗保健中的人工智能
背景情况:
- 病理学部门越来越多地采用数字化工作流程.
- 人工智能 (AI) 预计将在常规诊断中发挥重要作用.
- 这项研究侧重于人工智能在前列腺活检分析中的应用.
研究的目的:
- 描述AI在病理学中的实际应用.
- 评估人工智能对前列腺活检诊断的影响.
- 为未来的人工智能部署收集实际见解.
主要方法:
- 将前列腺活检分析的AI工具集成到现有的实验室信息和报告系统中.
- 将人工智能工具嵌入到安特卫普ZAS医院病理学系的日常工作流程中.
- 监测了实施过程,并收集了实用的见解.
主要成果:
- 减少了前列腺活检所需的免疫组织化学测试的数量.
- 实现了显著减少活检评估的周转时间.
- 观察到可测量的诊断信心和效率的改善.
结论:
- 第一年的人工智能集成在诊断效率和工作流程优化方面显示出明显的好处.
- 在现实世界中部署带来了挑战,包括人员适应和系统集成.
- 战略规划,培训和系统兼容性对于在病理学中成功采用人工智能至关重要.
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