Active-learning screening that reorders records as you decide
SWIFT-Active Screener is a web-based, collaborative software application that helps teams perform the screening process of systematic literature reviews more efficiently using active learning machine learning models.As screeners manually include or exclude articles, the underlying machine learning model continuously updates itself in real time. This iterative process learns from user feedback to prioritize and push the most likely relevant, unscreened articles to the top of the list, significantly reducing the manual screening burden.
