| Research

Millions of Flow Cytometry Datasets Are Useless for AI — Here's Why, and What It Would Take to Fix It

NIST, FDA, and NIAID convened a workshop revealing millions of flow cytometry datasets are unusable for AI due to metadata chaos.

Millions of Flow Cytometry Datasets Are Useless for AI — Here's Why, and What It Would Take to Fix It

Listen to this research

References

  1. [1] NIST/FDA/NIAID AI and Flow Cytometry Workshop https://www.nist.gov/news-events/events/2025/06/ai-and-flow-...
  2. [2] AI and Flow Cytometry — Lin et al. (J Immunol 2025) https://www.nist.gov/publications/ai-and-flow-cytometry
  3. [3] Robust FCS Parsing: 211,359 Files — Bras (Cytometry A 2020) https://onlinelibrary.wiley.com/doi/full/10.1002/cyto.a.2418...
  4. [4] ML framework for cross-institute AML classification (2025) https://www.sciencedirect.com/science/article/pii/S001048252...
  5. [5] Robinson et al. BioEssays 2026 https://onlinelibrary.wiley.com/doi/10.1002/bies.70091
  6. [6] Yue — AI in flow cytometry (Cytometry B 2025) https://onlinelibrary.wiley.com/doi/10.1002/cyto.b.22255
  7. [7] NIST Flow Cytometry Standards Consortium https://www.nist.gov/programs-projects/nist-flow-cytometry-s...
  8. [8] NIST FCSC WG5: AI/ML https://www.nist.gov/mml/bbd/fcsc-membership/fcsc-working-gr...
  9. [9] ML Methods in Clinical FCM (Cancers 2025) https://www.mdpi.com/2072-6694/17/3/483

🔬

About this article

This research article was synthesized by Dusk Agent using PubMed papers and Google Search grounding. Sources are linked to their original PubMed entries for verification. View all research articles.