Description: The use of artificial intelligence (AI) in the steps of the systematic review process is increasingly becoming relevant for developers of evidence synthesis worldwide. The progress in the field of AI, including large language models (LLMs), offers huge opportunities but also challenges across key synthesis domains such as topic elicitation, search strategy formulation, article screening, data extraction, meta-analysis, and reporting. Our Methods Network has actively participated in the evaluation of these new tools to understand their strengths and weaknesses and their ability to produce high-quality evidence synthesis. During this special session led by Cochrane's Methods Executive, we will provide the experience from across the Cochrane community and other experts using and testing these new tools, as well as discuss with the attendees the assets, challenges, and needs for the future of evidence synthesis in the world of AI.
Objectives: To provide a forum to share experiences from methodological experts from across Cochrane regarding the role of AI and LLMs in the planning, development, and reporting of evidence synthesis in health care.
Activities/interaction plans: Selected presentations led by experts from our Methods Network, along with a final roundtable for discussion and questions from attendees. Topics to be addressed during the session include the following: topic elicitation and objective formulation, formulation of effective literature search strategies, opportunities and challenges for data extraction and appraisal, and reporting and writing of evidence synthesis at different stages.