A head-to-head comparison of the accuracy of commercially available large language models for infection prevention and control inquiries, 2024
Year: 2024
Type: article
Abstract: We investigated the accuracy and completeness of four large language model (LLM) artificial intelligence tools. Most LLMs provided acceptable answers to commonly asked infection prevention questions (accuracy 98.9%, completeness 94.6%). The use of LLMs to supplement infection prevention consults should be further explored.
DOI: 10.1017/ice.2024.205
Institutions: University of Iowa Health Care, Stanford University
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,450
OpenAlex ID: W4405332363