Artificial intelligence (AI) technologies have the potential to transform cytopathology practice, and it is important for cytopathologists to embrace this and place themselves at the forefront of implementing these technologies in cytopathology. This review illustrates an archetypal AI workflow from project conception to implementation in a diagnostic setting and illustrates the cytopathologist's role and level of involvement at each stage of the process. Cytopathologists need to develop and maintain a basic understanding of AI, drive decisions regarding the development and implementation of AI in cytopathology, participate in the generation of datasets used to train and evaluate AI algorithms, understand how the performance of these algorithms is assessed, participate in the validation of these algorithms (either at a regulatory level or in the laboratory setting), and ensure continuous quality assurance of algorithms deployed in a diagnostic setting. In addition, cytopathologists should ensure that these algorithms are developed, trained, tested and deployed in an ethical manner. Cytopathologists need to become informed consumers of these AI algorithms by understanding their workings and limitations, how their performance is assessed and how to validate and verify their output in clinical practice.

中文翻译：

---

细胞病理学家在细胞病理学实践中开发和评估人工智能的作用。

人工智能 (AI) 技术具有改变细胞病理学实践的潜力，对于细胞病理学家来说，接受这一点并将自己置于在细胞病理学中实施这些技术的最前沿非常重要。本综述阐述了从项目概念到在诊断环境中实施的典型 AI 工作流程，并说明了细胞病理学家在该过程的每个阶段的作用和参与程度。细胞病理学家需要发展并保持对 AI 的基本了解，推动有关 AI 在细胞病理学中的开发和实施的决策，参与用于训练和评估 AI 算法的数据集的生成，了解如何评估这些算法的性能，参与这些算法的验证（在监管层面或在实验室环境中），并确保在诊断环境中部署的算法的持续质量保证。此外，细胞病理学家应确保以合乎道德的方式开发、培训、测试和部署这些算法。细胞病理学家需要成为通过了解这些 AI 算法的工作原理和局限性、如何评估其性能以及如何在临床实践中验证和验证其输出，让消费者了解这些 AI 算法。