Date: August 1, 2024
Time: 1:00 PM – 5:00 PM
Location: Chicago
Hosted by: Association for Diagnostics & Laboratory Medicine (ADLM)
The 2024 ADLM Data Science Symposium brought together leading experts in laboratory medicine and data science for an afternoon of cutting-edge presentations and discussions on AI applications in diagnostics, data-driven quality improvement, and lab utilization analytics.
Welcome
Anthony Killeen, University of Minnesota
ADLM Data Science
Patrick Mathias, University of Washington
Navigating the Changing Regulatory Landscape for AI in Clinical Diagnostics
Robert Benirschke (Moderator), Northshore University HealthSystem
Rezwan Ahmed, Roche Diagnostics
Ulysses Balis, University of Michigan
David Bussian, Pattern Bioscience
Bobby Reddy, Prenosis
Deep Reinforcement Learning for Cost-Effective Medical Diagnostic Testing
Yuan Luo, Northwestern University
Using Geospatial Tools to Analyze Equity in Access to Laboratory Testing
Vahid Azimi, Washington University in St. Louis
Use of Large Language Models to Generate Preliminary Drug Screen Sign-Outs
Brody Foy, University of Washington
Current and Future Perspectives on Data Use in Laboratory Medicine
Sarah Wheeler (Moderator), University of Pittsburgh
Shannon Haymond, Lurie Children's Hospital
Randal Schneider, Abbott
Tapan Shah, Siemens Healthineers
Stacia Sump, Clinisys
Forget EP Evaluator: Customizable Reports with R and Python
Rajeevan Selvaratnam, University Health Network
Ensemble Learning Allows for Detection of Significant Intravenous Fluid Contamination in Basic Metabolic Panels Missed by Current Methods
Nicholas Spies, ARUP Laboratories
Containerization and the Clinical Laboratory
Dustin Bunch, Nationwide Children's Hospital
Celiac Testing Algorithm Normalizes the Rate of Biopsies and Positivity
Lee Schroeder, University of Michigan
Closing
Tylis Chang, Northwell Health
Patrick Mathias, University of Washington
Interested in sponsorship opportunities? Contact [email protected] for information.
