Evaluation reveals a large language model reduces workload in surgical site infection adjudication, suggesting a path to improve accuracy.
Our study evaluated a large language model (gpt-4o-mini) for surgical site infection (SSI) adjudication, achieving 100% sensitivity but 69.4% specificity. While reducing the manual screening workload by 66%, the agent generated many false positives, underscoring the need for refined models to improve specificity without compromising accuracy.
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Miranti et al. (2026) studied this question.
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