Lewis A. Hassell, MD (Senior), Marika L. Forsythe, MD, Ami Bhalodia, MD, Thanh Lan, Tasnuva Rashid, MD, PhD, Astin Powers, MD, Marilyn M. Bui, MD, PhD, Arlen Brickman, MD, Qiangqiang Gu, PhD, Andrey Bychkov, Ian Cree, Liron Pantanowitz
Abstract
The introduction of new diagnostic information in pathology requires effective dissemination and adoption strategies. While traditional methods like journals, meetings, and atlases have been used, they pose challenges in accessibility, interactivity, and performance validation. Digital pathology (DP) and artificial or augmented intelligence (AI) offer promising solutions to address these limitations.
This paper advocates the use of DP and AI tools to facilitate the introduction of new diagnostic information in pathology. It highlights the importance of standardized training and validation sets, digital slide libraries, and AI-enhanced diagnostic tools. While AI can improve efficiency and accuracy, it's crucial to address potential pitfalls such as over-reliance on AI, bias and the need for human oversight.
By leveraging DP and AI, the efficiency and accuracy of diagnosis, grading, staging, and classification can be augmented, ultimately improving patient care.
2025; Published in Modern Pathology
