Artificial Intelligence and Automation in Evidence Synthesis: An Investigation of Methods Employed in Cochrane, Campbell Collaboration, and Environmental Evidence Reviews.

ABSTRACT: Automation, including Machine Learning (ML), is increasingly being explored to reduce the time and effort involved in evidence syntheses, yet its adoption and reporting practices remain under-examined across disciplines (e.g., health sciences, education, and policy). This review assesses the use of automation, including ML-based techniques, in 2271 evidence syntheses published between 2017 and 2024 in the Cochrane Database of Systematic Reviews, and the journals Campbell Systematic Reviews, and Environmental Evidence. We focus on automation across four review steps: search, screening, data extraction, and analysis/synthesis. We systematically identified eligible studies from the three sources and developed a classification system to distinguish between manual, rules-ba

SUBMITTER: Scotti KL 

PROVIDER: S-EPMC12407283 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature