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Assessing ChatGPT’s Theoretical Knowledge and Prescriptive Accuracy in Bacterial Infections: a Comparative Study with Infectious Diseases Residents and Specialists

INFECTION(2024)

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Abstract
Advancements in Artificial Intelligence(AI) have made platforms like ChatGPT increasingly relevant in medicine. This study assesses ChatGPT’s utility in addressing bacterial infection-related questions and antibiogram-based clinical cases. This study involved a collaborative effort involving infectious disease (ID) specialists and residents. A group of experts formulated six true/false, six open-ended questions, and six clinical cases with antibiograms for four types of infections (endocarditis, pneumonia, intra-abdominal infections, and bloodstream infection) for a total of 96 questions. The questions were submitted to four senior residents and four specialists in ID and inputted into ChatGPT-4 and a trained version of ChatGPT-4. A total of 720 responses were obtained and reviewed by a blinded panel of experts in antibiotic treatments. They evaluated the responses for accuracy and completeness, the ability to identify correct resistance mechanisms from antibiograms, and the appropriateness of antibiotics prescriptions. No significant difference was noted among the four groups for true/false questions, with approximately 70
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Key words
ChatGPT,Bacterial infections,Artificial intelligence,Endocarditis,Abdominal infection,Pneumonia,Blood-stream infection,Infectious diseases,Antibiotic resistance,Antimicrobial stewardship
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