De-Mystifying AI: Artificial Intelligence Applications in Histology
Recorded On: 10/15/2020
In recent years, the term AI (Artificial Intelligence) has become a buzz word in the scientific community - particularly in Pathology. More often than not, scientists have been given a directive to investigate AI solutions with no real detail beyond that. AI can mean many different things in many different contexts. This workshop will help to define the term AI, and look at its application in various aspects of Pathology and Histology. By framing the concepts in a user-friendly manner, we can minimize some of the barriers to adoption and look at various levels of application. These will include: Deep learning networks designed to identify and eliminate artifacts in slide preparation, segment structures within tissue sections, identify cells and phenotypes, and identify pathology scores based on tissue morphology. By providing real time examples of using AI in practical Pathology and Histology applications, we can de-mystify the concept of AI and make it accessible to scientists both in and outside of the computer lab.
CEUs: This histology course is worth 1 continuing education credit. Course is available for 365 days from date of purchase.
Adam Smith specializes in digital pathology and image analysis workflows. He received is bachelor’s in Biology from Ursinus College, and honed his skills in histology and digital pathology at Merck & Co., Inc. Adam currently works for Indica Labs, Inc. where he is passionate about using creative problem solving to provide image analysis solutions to his customers.