Title: Deploying digital pathology to enable artificial intelligence: Understanding fundamental requirements, barriers and opportunities in digital pathology

Biography:

David McClintock is an associate CMIO of Michigan Medicine (Pathology Informatics), Director of Digital Pathology, Associate Director of Pathology Informatics and associate professor at the University of Michigan, USA. His primary clinical interests comprise operational pathology and clinical laboratory informatics including workflow analysis, Laboratory Information System (LIS) optimization, and improved integration of pathology and clinical laboratory data within the EHR and clinical research data warehouses. 

Abstract

For many, the promises of digital pathology (DP) to streamline workflows, improve laboratory quality and to improve patient care are not readily apparent, especially when faced with the high costs of deploying DP. Calculating return on investment from introducing yet another layer of complexity and handoffs in an already complicated surgical pathology process can be riddled with inaccuracies and assumptions, such as major laboratory personnel (FTE) savings, decreases in turn-around time, and increased potential business through digital consults. Recently, the application of machine learning and artificial intelligence (AI) to whole slides images has emerged as a primary use case for the adoption of large-scale digital pathology efforts. With AI, multiple use cases now exists, that have the potential to transform the way pathology is practiced, both within the anatomic pathology laboratory and the pathologist sign out workspaces. This talk will describe how, by understanding the fundamental requirements, barriers to adoption, and opportunities for future growth related to digital pathology, one will be able to successfully determine how to deploy this new technology to its greatest ability.