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Peer-Reviewed Study Validates ARUP AI That Outperforms Microscopy in Detecting Intestinal Parasites

Peer-reviewed data show higher sensitivity from a model trained on thousands of globally sourced samples.

Overview

  • The Journal of Clinical Microbiology reports 98.6% positive agreement after discrepancy review and 169 additional organisms detected beyond manual reads.
  • A limit-of-detection study found the system identified parasites in highly diluted samples, indicating improved detection at early or low parasite levels.
  • Training drew on more than 4,000 parasite-positive cases from laboratories in the United States, Europe, Africa and Asia across 27 parasite classes, including rare species.
  • ARUP expanded AI to wet-mount analysis in March 2025, becoming the first laboratory to apply AI across the entire ova-and-parasite testing workflow.
  • The AI-enabled workflow helped ARUP manage a record surge in parasite specimens in August without quality loss, and ARUP with Techcyte plans expansion beyond parasitology with Pap testing already assisted by AI.