Background: The incorporation of digital pathology into routine pathology practice is becoming more widespread. Definite advantages exist with respect to the implementation of artificial intelligence (AI) and deep learning in pathology, including cytopathology. However, there are also unique challenges in this regard. Summary: This review discusses cytology-specific challenges, including the need to implement digital cytology prior to AI; the large file sizes and increased acquisition times for whole slide images in cytology; the routine use of multiple stains, such as Papanicolaou and Romanowsky stains; the lack of high-quality annotated datasets on which to train algorithms; and the considerable computer resources required, in terms of both computer infrastructure and skilled personnel, for computing and storage of data. Global concerns regarding AI that are certainly applicable to cytology include the need for model validation and continued quality assurance, ethical issues such as the use of patient data in developing algorithms, the need to develop regulatory frameworks regarding what type of data can be utilized and ensuring cybersecurity during data collection and storage, and algorithm development. Key Messages: While AI will likely play a role in cytology practice in the future, applying this technology to cytology poses a unique set of challenges. A broad understanding of digital pathology and algorithm development is desirable to guide the development of algorithms, as well as the need to be cognizant of potential pitfalls to avoid when incorporating the technology in practice.
Acta Cytologica

中文翻译：

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在细胞学中开发深度学习算法的挑战

背景：将数字病理学纳入常规病理学实践正变得越来越普遍。在病理学（包括细胞病理学）中实施人工智能 (AI) 和深度学习具有绝对优势。然而，在这方面也存在独特的挑战。概括：本综述讨论了特定于细胞学的挑战，包括在 AI 之前实施数字细胞学的必要性；细胞学中整个载玻片图像的大文件大小和增加的采集时间；常规使用多种染色剂，例如巴氏染色剂和罗曼诺夫斯基染色剂；缺乏用于训练算法的高质量注释数据集；以及计算和存储数据所需的大量计算机资源，包括计算机基础设施和技术人员。全球对 AI 肯定适用于细胞学的担忧包括模型验证和持续质量保证的需要、道德问题，例如在开发算法时使用患者数据，关键信息：虽然未来人工智能可能会在细胞学实践中发挥作用，但将这项技术应用于细胞学会带来一系列独特的挑战。需要对数字病理学和算法开发有广泛的了解，以指导算法的开发，并且需要认识到在实践中结合该技术时要避免的潜在陷阱。
细胞学学报