Pandemic-Potential Viruses are a Blind Spot for Frontier Open-Source LLMs.

ABSTRACT: We study large language models (LLMs) for front-line, pre-diagnostic infectious-disease triage, a critically understudied stage in clinical interventions, public health, and biothreat containment. We focus specifically on the operational decision of classifying symptomatic cases as viral vs. non-viral at first clinical contact, a critical decision point for resource allocation, quarantine strategy, and antibiotic use. We create a benchmark dataset of first-encounter cases in collaboration with multiple healthcare clinics in Nigeria, capturing high-risk viral presentations in low-resource settings with limited data. Our evaluations across frontier open-source LLMs reveal that (1) LLMs underperform standard tabular models and (2) case summaries and Retrieval Augmented Generatio

SUBMITTER: Luebbert L 

PROVIDER: S-EPMC12706609 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature