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在计算癌症病理学的人机相互作用
A Syrnioti1, A Polónia2,3, J Pinto2
1Department of Pathology, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece.
概括
使用人工智能 (AI) 的增强病理学家显示出卓越的准确性. 解决信任,偏见和劳动力适应对于AI在病理学中的整合至关重要.
科学领域:
- 病理学 病理学 病理学
- 医疗人工智能 医疗人工智能
- 人与计算机的交互
背景情况:
- 人工智能 (AI) 在病理学工作流程中的整合正在迅速推进.
- 增强型病理学家,将人类专业知识与人工智能结合起来,越来越多地被认为是提高了诊断准确度.
- 关于信任,偏见和员工影响的担忧需要仔细考虑.
研究的目的:
- 为了评估增强病理学家的表现,与单独的AI和单独的病理学家相比.
- 在日常人工智能辅助病理学工作中,识别和解决与人机交互相关的挑战.
- 为人工智能在病理学中的可持续整合提出战略,包括劳动力教育和验证指南.
主要方法:
- 增强病理学家,仅使用人工智能的系统和人类病理学家的比较性能分析.
- 人机交互的定性评估,重点关注信任和偏见.
- 关于AI在病理学工作人员培训和验证方面的当前实践和文献的审查.
主要成果:
- 增强型病理学家比单独的AI和单独的病理学家更准确.
- 人机交互带来了与信任和潜在偏见有关的挑战.
- 病理学工作人员的非培训和更新教育课程的需要是严重的担忧.
结论:
- 病理学家和人工智能之间的协同作用提供了最高的诊断准确性.
- 需要采取积极的措施来管理信任,减轻偏见,防止劳动力失业.
- 为了保持高质量的癌症病理学,制定人工智能工具验证和验证的明确准则至关重要.
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