Figure 1.
AI capabilities across different stages of the systematic literature review (SLR) process_
| SLR step | Role of AI | Sources |
|---|---|---|
| Scoping analysis | Automates extraction of key information such as author names, affiliations, keywords, citation counts, and topics from research publications; analyzes citation networks to identify influential papers, predicts research impact, and identifies collaborations. | Saeidnia et al., 2024 |
| Research purpose and research questions | Identifies gaps in the literature, generates hypotheses, predicts correlations and causal relationships, and provides insights from existing trends and cross-disciplinary studies to help set new research directions. | Wagner et al., 2022; Saeidnia et al., 2024 |
| Research context identification | Processes large datasets to identify literature gaps, extract keywords, topics, and trends; generates ideas, hypotheses, and research problems; predicts emerging trends; detects potential collaborators; and measures impact and visibility. | Saeidnia et al., 2024; Khalifa & Albadawy, 2024 |
| Literature identification | Disambiguates authors; predicts publication trends and research impact; automatically collects bibliographic data; analyzes citation networks to identify influential papers, authors, and journals. | Saeidnia et al., 2024 |
| Literature selection | Provides efficient methods for text manipulation, knowledge representation, and inference; uses machine learning to automate decisions on the relevance of papers, supporting efficient and accurate literature-selection processes. | de la Torre-López et al., 2023; Ngwenyama & Rowe, 2024; Wagner et al., 2022 |
| Data extraction and synthesis | Automatically extracts information from articles using ML/DL/NLP methods, summarizes extracted data, creates tables and graphs, updates meta-analyses, and synthesizes data to create structured tables and diagrams summarizing evidence. | Santos et al., 2023; Amezcua-Prieto et al., 2020 |
| Reporting and recommendations preparation | Assists in grammar correction, text rewriting, recommendation generation, automatic identification of missing data, evidence synthesis, topic identification, and recommending relevant resources and collaborations based on user preferences. | Chemaya & Martin, 2023; Santos et al., 2023; Saeidnia et al., 2024 |