With the increasing implementation of digital cytology much interest has been generated in the application of artificial intelligence (AI) algorithms to cytology. While cytology has been early adopters of AI for screening cervical cytology specimens the field has been slower to adopt AI for non-GYN specimens. The introduction of whole slide imaging (WSI) to non-GYN cytology has created an opportunity for AI algorithms. The American Society of Cytopathology (ASC) along with the International Academy of Cytology and the Digital Pathology Association convened a task force to investigate digital cytology and AI applications. In this ASC companion session two experts from the task force will review the history of AI in cytology, present the current state of AI in cytology, and discuss what opportunities lie ahead for AI in cytology.

The rapid evolution of digital technology and artificial intelligence (AI) has ushered in a new era in surgical pathology practice, significantly transforming traditional methodologies. While digital cytology and AI have been slower to integrate compared to other fields, they are steadily gaining traction within cytology laboratories. Recognizing the significance of this shift, the American Society of Cytopathology (ASC) convened a digital cytology task force to assess the current state of digital cytology and AI adoption in the field. Through comprehensive research and analysis, the ASC task force has not only identified the existing landscape of digital cytology and AI in cytology but has also issued a set of recommendations aimed at validating the implementation of digital cytology and AI in cytology practice. These recommendations serve as a roadmap for laboratories seeking to leverage digital technologies to enhance their diagnostic capabilities and improve patient outcomes.This session aims to delve deeply into the critical aspects of the digital transformation of cytology practice. Attendees will gain a comprehensive understanding of how digital cytology and AI can be seamlessly integrated into their workflow, thereby optimizing efficiency and accuracy in diagnostic processes. By exploring the myriad benefits and challenges associated with digital cytology, participants will gain insights into how this technological revolution is reshaping the landscape of cytology practice. One of the key points of the session will be an exploration of the ways in which digital cytology and AI contribute to enhancing patient care. By streamlining workflows, facilitating collaboration among pathologists, and enabling more precise diagnoses, these technologies have the potential to significantly improve patient outcomes and overall healthcare delivery. Furthermore, the session will provide an overview of current AI models that are relevant to cytology. Attendees will gain valuable insights into the various development approaches employed in creating these models, ranging from traditional machine learning techniques to more advanced deep learning methodologies. By understanding the challenges and benefits associated with each approach, participants will be better equipped to evaluate and implement AI solutions in their own practice settings.In summary, this session offers a comprehensive exploration of the intersection between digital technology, artificial intelligence, and cytology practice. By providing attendees with practical insights and actionable recommendations, it seeks to empower pathologists to embrace and harness the transformative potential of these technologies, ultimately driving improvements in patient care and advancing the field of cytology.

Learning Objectives

1. To explore the advantages and obstacles of adopting digital cytology, emphasizing its pivotal role in improving patient care and advancing cytopathology practices.
2. To review guidelines for digital cytology integration, particularly concerning AI incorporation and the ethical considerations involved in these advances.         
3. To examine current AI models in cytology, discussing their development methods, challenges, and benefits to offer a comprehensive understanding of AI's impact on cytology.