2026 Data Science Symposium

Shape the future of laboratory data science.

Join the premier gathering of laboratory medicine professionals, data scientists, and healthcare innovators at the 2026 ADLM Data Science Symposium. Explore cutting-edge applications of data science in laboratory medicine and connect with thought leaders transforming the field. The 2026 ADLM Data Science Symposium will be held immediately after ADLM's Annual Meeting in Anaheim on July 30 this year. It will feature a keynote speaker, a panel, a poster presentation showcase with the Data Science and Informatics Division, and lightning talks.

How to Register

Registration is free for both ADLM members and nonmembers. There are two registration options.

Option 1: To attend the Data Science Symposium only (without the full Annual Meeting), select “Special Events Only” during registration (Step 3 in the registration process).
Option 2: To attend the full Annual Meeting, use the standard Annual Meeting registration option.
For both options, on Step 4, search for the session type “Special Events” and select 80 Data Science Symposium.

Theme: Delivering value with laboratory data science

Learning objectives

Compare and contrast different data science tools.
Explore gaps in the value proposition of laboratory data science.
Leverage local resources to realize value using laboratory data science.

Why attend?

Learn from expert-led sessions on AI/ML applications in laboratory medicine.
Network with data scientists, informaticists, and laboratory leaders.
Discover emerging trends in laboratory data science.
Stay updated. Receive symposium updates. Sign up here.

Data Science Symposium Agenda

Time

Session

Speaker(s)

1–1:15 p.m.

Welcome and Community Context

Sarah Wheeler, PhD

1:15–1:45 p.m.

Keynote Address

Keynote Speaker (Dr. Brian Jackson, University of Maryland)

1:45–2 p.m.

Keynote Q&A

Moderated by Chris McCudden, PhD

2–2:30 p.m.

Networking and Data Science Poster Showcase
Featuring the Data Science & Informatics Division

Poster presenters picked by the ADLM
Data Science & Informatics Division

2:30–3:05 p.m.

Panel Discussion: Regulatory and
Quality Compliance in Laboratory Medicine AI

Panelist (Nick Trentadue, Epic)

Panelist (Dr. Michael King, Roche Diagnostics)*

Panelist (Sarina Yang, PhD, Weill Cornell Medicine)

Moderated by ADLM's Data Analytics Steering Committee

3:05–3:45 p.m.

Lightning Talks – Session 1

Moderator: Ming Jin, PhD

Machine Learning–Enhanced Diagnostic Performance of Plasma Metanephrines in PPGL: A Large-Scale Real-World Clinical Cohort Study

AI-R Apparent: Using artificial intelligence and refineR on big data to unmask chloride-driven anion gap differences across a multi-laboratory, multi-platform enterprise

Estimation of post-transplant glomerular filtration rate in living kidney transplant recipients determined by pre-transplantation characteristics

3:45–4 p.m.

Networking Break and Poster Continuation

—

4–4:45 p.m.

Lightning Talks – Session 2

Moderator: Li Zha, PhD

Automating Reports To Monitor Laboratory Stability and Defects

DAEDALUS: a de novo artificial intelligence co-designed bioinformatics pipeline for infectious disease next-generation sequencing applications

Real-World Evaluation of Service Flow Redesign Using Proprietary AI Sentiment Analysis in a Clinical Diagnostics Support Channel

4:45–5 p.m.

Closing Remarks and Next Steps

Sarah Wheeler, PhD

*Presenting in personal capacity and not on behalf of Roche

Become a symposium sponsor

Position your organization as a leader in laboratory data science. Connect with laboratory scientists and data science professionals shaping the future of laboratory medicine.

Contact: [email protected]