LabQAR (LaboratoryQuestionAnswering withReference Ranges) Data Set

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Authors: Balu Bhasuran, Zhe He
Cited by: 0

Abstract

LabQAR (Laboratory Question Answering with Reference Ranges), a manually curated dataset containing multiple-choice questions about 550 lab tests with comprehensive reference ranges sourced from trusted medical resources with annotations on reference ranges, specimen types, and other factors impacting interpretation. We also assess the performance of several large language models (LLMs), including LLaMA 3.1, GatorTronGPT, GPT-3.5 turbo, GPT-4 turbo, and GPT-4o, in predicting reference ranges and classifying results as normal, low, or high.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Clinical Laboratory Practices and Quality Control Machine Learning in Healthcare

Publication details

Journal / source
Figshare
Publication date
1 January 2026
Document type
Dataset