Artificial Intelligence

A free-to-use, open-source systematic review assistant that leverages state-of-the-art active learning techniques in order to help review large amounts of articles/content for specific key words and qualifiers. Originally developed by a team of researchers from Utrecht University, the software is now part of a non-profit initiative driven by multidisciplinary researchers and system engineers from across the country. Free to download and use.

Pulling from publisher partnerships, data providers, and web crawls, this AI-driven search and discovery toolset provides a streamlined search platform for over 200 million academic papers. Developed within the Allen Institute for AI, this open project has been worked on since 2015 with the goal of supporting high-quality research. Free to use.

This online platform generates brand new summaries and findings that are created using an AI reviewer and the contents of each respective paper. Developed by the Ought non-profit learning research lab, the system helps researchers find papers to cite and defined research directions. It currently provides both summary services in addition to an in-depth literature review toolset, all sourced through the over 200 million academic papers available through Semantic Scholar. Free to use.

Using a complex AI-backed methodology, this platform is a literature mapping tool. Using a “seed” article, the platform finds relevant articles and content to link. Visualized by a bubble map of connected topics, this toolset can be invaluable for finding additional connections across a variety of disciplines as well as staying up to date with up and coming publications. This initiative is supported by a development collective, which has pledged to keep the core discovery functionalities open for all to use. Sign up required to access at researchrabbit.ai. Free to use.