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      • AI-powered tools like machine learning algorithms and natural language processing (NLP) can significantly streamline finding relevant literature. These tools can search extensive databases and digital libraries to identify articles, books, and papers that match specific keywords and topics.
      atlasti.com/guides/literature-review/literature-review-ai
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  2. Aug 17, 2024 · This paper presents a comprehensive review of the use of Artificial Intelligence (AI) in Systematic Literature Reviews (SLRs). A SLR is a rigorous and organised methodology that assesses and integrates prior research on a given topic. Numerous tools have been developed to assist and partially automate the SLR process.

    • Francisco Bolaños
  3. Oct 8, 2021 · We conclude this section by outlining four aspects relevant to AI-based tools across the six steps of the literature review process: (1) evaluation and validity, (2) transparency and replicability, (3) compatibility for recombination, and (4) usability.

    • Gerit Wagner, Roman Lukyanenko, Guy Paré
    • 2021
  4. Oct 8, 2024 · This guide shows you how you can use AI tools to help with aspects of the literature review process: Abstract and title creation. Scoping and protocol development. Searching. Screening. Data extraction. Synthesis.

  5. The most popular tools that use advanced generative AI to support literature review are Elicit, Scite AI and, to a lesser extent (as it’s designed for global searching not just scholarly databases), Perplexity AI.

  6. Oct 18, 2024 · There are a growing number of AI tools available to support different parts of the literature review process, including generating new keyword ideas, providing context for citations, summarizing sources, and creating visualizations of the connections between sources. We chose to review tools that fit the following criteria:

  7. AI-powered tools can quickly identify relevant studies, extract key themes and concepts, and even generate summaries. In recent years, using AI for literature reviews has gained significant importance in academic research.

  8. Jun 9, 2022 · relevant to AI-based tools across the six steps of the lit- erature review process: (1) evaluation and validity, (2) transparency and replicability, (3) compatibility for re-