Why You Shouldn’t Select an AI System Based on Performance in Pathology

The rise of digital pathology is shifting this standard of care from microscope to image. And in doing so, it’s opening new opportunities to drive efficiency, unlock new insights, and deliver better patient care, including the introduction of computational methods. AI systems have come online to process biopsy images – with applications that prioritize the most urgent cases for review, highlight regions of cancerous tissue, and quantify tumor cells among addressing other use cases. Yet not every AI system will be impactful. As Proscia’s VP of AI R&D Julianna Ianni, Ph.D. explains even AI systems that perform well on paper will fail in the clinic.