MUSM Clinical Faculty Development Series

Describe how AI tools (e.g., ClinicalKey AI, OpenEvidence, PubMed-integrated tools) support literature discovery through summarization and semantic search Differentiate AI-assisted searching from traditional bibliographic database searching (e.g., Web of Science, Embase) with respect to completeness, reproducibility, and bias Apply structured strategies to translate AI-generated insights into reproducible search strategies (e.g., MeSH, Boolean logic) Identify risks of AI use in scholarly work, including hallucinations, citation inaccuracies, and incomplete retrieval Implement best practices for responsible AI use in literature reviews, including verification, citation integrity, and disclosure.