Practical considerations in evaluating and implementing AI solutions for today’s clinical laboratorian

Course ID: 191307
6.0 ACCENT credits /6.0 CME credits
Sunday, July 26, 2026
All day course | 9 a.m. – 4 p.m. US Pacific Time
Anaheim Marriott (next to Anaheim Convention Center)

Artificial intelligence (AI) solutions are poised to revolutionize the daily operations of the clinical laboratory. As these applications become more commonplace in our literature and our laboratories, it is crucial that we familiarize ourselves with how best to evaluate and implement them. This session will equip laboratorians with the fundamentals needed to help guide their institution's AI strategy. Participants at any level of expertise are welcome, and no technical background or programming skills will be required. This course will explore the key aspects of evaluating and implementing AI in laboratory medicine. Participants will learn to critically appraise AI literature, identify practical use cases, design validation studies, and navigate implementation, governance, and regulatory considerations. Through interactive case studies on a companion website, participants will gain hands-on experience applying these concepts to real-world scenarios.

Faculty

Moderator: Patrick Mathias, PhD, MD, University of Washington School of Medicine
Amrom Obstfeld, MD, PhD, Children's Hospital of Philadelphia
Nicholas Spies, MD, University of Utah/ARUP Laboratories
Brody Foy, DPhil, University of Washington
Michelle Stoffel, MD, PhD, M Health Fairview/University of Minnesota

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Course details

Target audience

Advanced practice professionals (NPs, PAs, RNs, etc.); Lab supervisors; Lab directors (and/or assistant directors); Lab managers (supervisory and/or non-supervisory); Medical technologists; Point-of-Care coordinators; Physicians; Pathologists; Toxicologists; In-training individuals
Presentation level

Basic
What to bring

A laptop or personal device for notetaking and audience participation. Please note that charging stations are not available at audience tables, bring a fully charged device for this activity.
Learning objectives and skills you will gain
After participating in this course, participants will be able to:
- Appraise literature describing AI solutions to laboratory problems.
- Evaluate AI model performance and identify common pitfalls.
- Contribute subject-matter expertise to implementation efforts at their own institutions.
Faculty
- Moderator: Patrick Mathias, PhD, MD, University of Washington School of Medicine
- Amrom Obstfeld, MD, PhD, Children's Hospital of Philadelphia
- Nicholas Spies, MD, University of Utah/ARUP Laboratories
- Brody Foy, DPhil, University of Washington
- Michelle Stoffel, MD, PhD, M Health Fairview/University of Minnesota

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