With digital equipment and workflows now proliferating in pathology laboratories, the next technological leap is the introduction of artificial intelligence. Here, Dr Kayla Hackman MD, Benjamin Dyer and Hallie Rane look at the roles for AI in clinical and diagnostic workflows.
Anatomic pathology is undergoing a significant transformation with the advent of artificial intelligence (AI). Advances in computer vision and deep-learning methodologies have resulted in AI tools capable of performing tasks traditionally completed by humans, such as slide quality control, immunohistochemistry (IHC) expression analysis, cancer diagnosis and grading, and tumour estimation for slide macrodissection. The increasing adoption of digital pathology scanners in clinical and research laboratories, the availability of AI tools in the life sciences, and the decreasing cost of storing whole-slide image (WSI) data have facilitated the creation of large, diverse data sets suited for AI analysis. At the same time, the growing complexity of pathology cases and the worsening shortage of pathologists have created a pressing need for methods that automate and expedite the diagnostic process; a problem AI is uniquely situated to address.1
This article discusses some of the current and potential applications of AI in the field of clinical and diagnostic digital pathology and makes the case for an AI-augmented pathologist empowered to do more through AI assistance.
Benefits of AI
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