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A Retrieval-Based Approach for Automatic Interpretation of Multi-Analyte Laboratory Profiles.

Thomas E Tavolara1, Sarthak Khandelwal1, Rachel Leger2

  • 1Division of Computational Pathology and Artificial Intelligence, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States.

The Journal of Applied Laboratory Medicine
|May 26, 2026
PubMed
Summary
This summary is machine-generated.

Automating lupus anticoagulant (LAC) profile interpretation with a novel retrieval-based approach significantly enhances efficiency. This method provides accurate and reliable results, reducing interpretation time by over 78%.

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Published on: September 23, 2021

Area of Science:

  • Medical Informatics
  • Clinical Laboratory Science
  • Artificial Intelligence in Medicine

Background:

  • Interpreting multi-analyte laboratory profiles, like lupus anticoagulant (LAC) testing, is complex, time-consuming, and requires significant expertise.
  • Existing rule-based systems are rigid and difficult to maintain, while large language models risk inaccuracies.
  • A novel retrieval-based approach was developed to automate LAC profile interpretation, aiming for improved efficiency, fidelity, and reliability.

Purpose of the Study:

  • To develop and evaluate a novel retrieval-based approach for automating lupus anticoagulant (LAC) profile interpretation.
  • To improve the efficiency and scalability of complex laboratory profile interpretation.
  • To maintain high fidelity and reliability in clinical decision-making.

Main Methods:

  • Laboratory values were processed using ensemble random forest (RF) models.
  • The system retrieved similar expert interpretations from a database of 347 previously interpreted LAC profiles.
  • Performance was assessed via technical accuracy, workflow efficiency studies, and expert review.

Main Results:

  • Technical validation showed high accuracy in retrieving interpretative elements (median 93%).
  • Automated interpretation reduced reporting time by 78.6% (median 22s vs. 118s manually).
  • Expert review confirmed 100% concordance for LAC presence/absence.

Conclusions:

  • The novel retrieval-based approach significantly enhances the efficiency of LAC profile interpretation.
  • The method maintains consistency and high fidelity, suitable for clinical use.
  • Future work will explore extending this approach to other multi-analyte laboratory profiles.