Curious about the future of evidence synthesis? Join Margaret Foster and the experts from The Center for Systematic Reviews and Research Syntheses at the Medical Sciences Library, Texas A&M University, for an insightful and informal session on systematic reviews!
The first part of the presentation will provide an update on emerging standards and best practices for integrating artificial intelligence (AI) into systematic reviews. Discover practical workflows and applications, along with a frank discussion of the challenges involved.
The remainder of the session will be dedicated to answering your questions about systematic reviews, ensuring you leave with valuable insights. Don't miss this opportunity to stay at the forefront of systematic review methodology!
*A link will be provided to those who register to submit questions in advance.
Speaker Information
Margaret J. Foster, MS, MPH is the Evidence Synthesis and Scholarly Dissemination Librarian and the Head of the Center for Systematic Reviews and Research Syntheses at the Medical Sciences Library, Texas A&M University. She is the co-author of Piecing Together Systematic Reviews and Other Evidence Syntheses (2022). She received the Lucretia W. McClure Excellence in Education Award in 2024 from the Medical Library Association.
Kyle M. Holland is an information specialist with the Center for Systematic Reviews and Research Syntheses at the Texas A&M University Medical Sciences Library. He specializes in systematic searching and bibliographic data manipulation.
Esmeralda G. Rodgers, MLIS, AHIP, serves as an Evidence Review & Synthesis Librarian at the Texas A&M University Medical Sciences Library. Her work focuses on expert literature searching and providing comprehensive guidance to researchers conducting evidence synthesis projects
Dani LaPreze, MLS, MS, is an Evidence Review & Synthesis Librarian. She leads and collaborates with interdisciplinary research teams at the Texas A&M University Medical Sciences Library, specializing in advanced literature searching and strategic support for evidence synthesis initiatives. Her role emphasizes hands-on research expertise and effective team coordination throughout the review process.
This class is for educational and informational purposes in alignment with NNLM goals and does not offer medical advice.
By registering for this class, you are agreeing to the NNLM Code of Conduct
- Discuss standards and best practices for using AI for systematic reviews.
- Explain the integration of AI into review project workflows.
- Identify challenges in using AI in systematic reviews.