Evaluation of Large Language Models in Infectious Disease Decision-Making: From Examination to Clinical Practice
Dandan Wu, Keying Chen, Xiaocui Wu, Jiongfei Jin, Feng Xu · 2026
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Description
Dandan Wu is lead author of a 2026 journal article testing four large language models, the kind of AI behind chatbots, on infectious disease decision-making. The models were DeepSeek-R1, ChatGPT-5, Grok 3, and Gemini 2.5 Flash, and their answers were compared with those of trainee infectious disease doctors.
On examination questions, the models matched the residents on accuracy and scores, doing somewhat better on fact-based questions and worse on simple case questions. On ten real clinical cases, expert reviewers rated model answers highly for accuracy, completeness, and safety. Doctors aided by a model scored higher on completeness than either doctors alone or models alone, the clearest gain found.
Catalog record
| CREATOR | Dandan Wu, Keying Chen, Xiaocui Wu, Jiongfei Jin, Feng Xu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 39430 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |