Summary of Artificial Intelligence For Literature Reviews: Opportunities and Challenges, by Francisco Bolanos et al.
Artificial Intelligence for Literature Reviews: Opportunities and Challenges
by Francisco Bolanos, Angelo Salatino, Francesco Osborne, Enrico Motta
First submitted to arxiv on: 13 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Human-Computer Interaction (cs.HC); Information Retrieval (cs.IR)
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Summary difficulty | Written by | Summary |
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High | Paper authors | High Difficulty Summary Read the original abstract here |
Medium | GrooveSquid.com (original content) | Medium Difficulty Summary In this comprehensive review, researchers examine the growing role of Artificial Intelligence (AI) in Systematic Literature Reviews (SLRs), a methodology used to assess previous research on a given topic. The study focuses on how AI techniques are applied in the semi-automation of SLRs, specifically in the screening and extraction phases. By analyzing 21 leading SLR tools and 11 recent tools leveraging large language models, researchers identify current trends, challenges, and future research directions. |
Low | GrooveSquid.com (original content) | Low Difficulty Summary Artificial Intelligence is helping scientists make sense of a huge amount of information. Systematic Literature Reviews (SLRs) are a way to combine findings from many studies on the same topic. Researchers are using AI to help with SLRs by making it easier to find relevant articles and summarize what they say. In this study, experts looked at 21 tools that can help with SLRs and 11 new tools that use artificial intelligence to search for information and write reports. They found out what’s working well and what still needs improvement. |