acePerformance comparison of physicians and large language models in tuberculosis triage, differential diagnosis, and management: a vignette-based comparative study
BACKGROUND Tuberculosis (TB) remains a major global health challenge, particularly in low- and middle-income countries, where effective triage, diagnosis, and management are often limited. Existing decision-support tools focus on imaging and cannot integrate multi-modal clinical information, constraining their utility in complex clinical scenarios. Large Language Models (LLMs) have shown promise in assisting diagnosis and clinical decision-making in other medical fields, but evidence for their application in TB…
In a study of 17 tuberculosis cases, ChatGPT-4o and DeepSeek-R1 beat two TB physicians on management recommendations, with recall of 0.50 versus 0.20 and F1 of 0.50 versus 0.30.
The study used only 17 standardized cases, 7 of them simulated, and involved no patient interventions or randomization, so real-world effects on care were not tested.
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- Peer-reviewedBMC Infectious Diseases2026-11-06
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Truvace Impact Record TRV-2026-2421, v1: “Performance comparison of physicians and large language models in tuberculosis triage, differential diagnosis, and management: a vignette-based comparative study.” Truvace, 2026-11-08. /record/TRV-2026-2421 (accessed on the day you copy it). sha256 8740c486c5623ab2…
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