# Recent Applications of Explainable AI (XAI): A Systematic Literature Review
## 3 Research Methodology  
Based on the research questions posed in Section 1 and the different taxonomies of XAI described in Section 2, we initiated our systematic review on recent applications of XAI. To collect the relevant publications for this review, we followed the analytical protocol of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA)  
Figure 1: Overview of different XAI approaches and evaluation methods. These categories were used to classify the XAI application papers reviewed in this study. guidelines [37]. A systematic review \"is a review of a clearly formulated question that uses systematic and explicit methods to identify, select, and critically appraise relevant research, and to collect and analyze data from the studies that are included in the review\" [12]. According to the PRISMA guidelines, our evaluation consisted of several stages: defining eligibility criteria, defining information sources, presenting the search strategy, specifying the selection process, data collection process, data item selection, studying the risk of bias assessment, specifying effect measures, describing the synthesis methods, reporting bias, and certainty assessment [37]. _Information sources and search strategy:_ The search was conducted in February 2024 on Web of Science (WoS) by using the following Boolean search string on the paper topic (note that searches for topic terms in WoS search the following fields within a record: Title, Abstract, Author Keywords, Keywords Plus): TS = ((\"explainable artificial intelligence\" OR XAI) AND (application\" OR process\")). The asterisk (\") at the end of a keyword ensures the inclusion of the term in both singular and plural forms and its derivatives. The search was limited to English-language non-review articles published between 1 January 2021 and 20 February 2024 (the search results can be found here: [[https://www.webofscience.com/wos/woscc/summary/495b659d-8f9e-4b77-8671-2](https://www.webofscience.com/wos/woscc/summary/495b659d-8f9e-4b77-8671-2) fac26682231-cda1 ce8b/relevance/1]([https://www.webofscience.com/wos/woscc/summary/495b659d-8f9e-4b77-8671-2](https://www.webofscience.com/wos/woscc/summary/495b659d-8f9e-4b77-8671-2) fac26682231-cda1 ce8b/relevance/1), accessed on 24 September 2024). We exclusively used WoS due to its authoritative status and comprehensive coverage. Birkle et al. (2020) [38] highlight WoS as the world's oldest and most widely used research database, ensuring reliable and high-quality data. Its extensive discipline coverage and advanced citation indexing make it ideal for identifying influential works and mapping research trends [38]. _Eligibility criteria and selection process:_ The literature selection process flow chart is summarized in Figure 2. The database search produced 664 papers. After removing non-English articles (\(n=4\)), 660 were eligible for the full-text review and screening. During the full-text screening, we implemented the inclusion and exclusion criteria (Table 1) established through iterative discussions among the two authors. The reviewers assessed each article under the inclusion and exclusion criteria, with 512 research articles meeting the inclusion criteria and being incorporated into the evaluation procedure. As reported in Figure 2, five articles were not retrievable from our universities' networks, and 143 were excluded because they did not meet our inclusion criteria (primarily because they introduced general XAI taxonomies or new methods without describing specific XAI applications). Consequently, 512 articles remained for data extraction and synthesis. For reasons of reproducibility, the entire list of included articles is attached