Artificial Intelligence and Machine Learning for Intestinal Parasite Detection: Machines Helping Make Humans Better Since 2019

 

Artificial intelligence (AI) is a recent tool for clinical pathology and clinical microbiology specifically for integration with diagnostic care. What can AI and computer vision do for microbiology? In the world of parasitology, we have developed and integrated the world’s first AI model which augments the technologist’s workflow to aid in detection of intestinal protozoa. AI model and computer vision integration makes the work of detecting protozoa from stool faster, more sensitive, and more enjoyable. This presentation will explore the current technology deployed in our laboratory as well as provide a sneak peek at the next generation AI model for additional detection of less common protozoa.

Originally published on April 11, 2022

Lecture Presenter

Marc R. Couturier, PhD

Marc R. Couturier, PhD

Medical Director, Microbial Immunology; Medical Director, Parasitology and Fecal Testing; Medical Director, Infectious Disease Antigen Testing
ARUP Laboratories

Dr. Couturier is an associate professor of pathology at the University of Utah School of Medicine. He received his PhD in medical microbiology and immunology with a specialty in bacteriology from the University of Alberta in Edmonton, Alberta, Canada. Dr. Couturier served as a research associate/post-doctoral fellow at the Alberta Provincial Laboratory for Public Health and completed a medical microbiology fellowship (ABMM) at the University of Utah. His research interests include Helicobacter pylori diagnostics and population prevalence, in particular identifying populations with increased risk of infection and reduced access to medical care. Dr. Couturier also has a research focus aimed at developing improved diagnostics for emerging agents of infectious gastroenteritis. He is board certified in medical microbiology, and a member of the American Society for Microbiology and Infectious Disease Society of America. Dr. Couturier is the program director for the Medical Microbiology fellowship at the University of Utah/ARUP.

Objectives

After this presentation, participants will be able to:

  • Discuss the theory of AI and how models are trained
  • Recognize the role of AI in stool parasite detection for trichrome stains
  • Describe the future applications of AI in parasitology

Sponsored by:

University of Utah School of Medicine, Department of Pathology, and ARUP Laboratories