# Recent Applications of Explainable AI (XAI): A Systematic Literature Review
## 4 Results
### Application Domains
Social media monitoringfor xenophobic content detection [183] and the broader applications of intrusion detection and cybersecurity [184] highlight the diverse use of XAI in this domain. In the finance sector, XAI techniques have been employed to enhance various decision-making processes. Research has focused on decision-making in banking and finance sector applications [185], asset pricing [186], and predicting credit card fraud [187]. Studies have also aimed at predicting decisions to approve or reject loans [188] and addressing a range of credit-related problems, including fraud detection, risk assessment, investment decisions, algorithmic trading, and other financial decision-making processes [189]. Credit risk assessment has been a significant area of research, with studies on credit risk assessment [190], predicting loan defaults [191], and credit risk estimation [192, 193]. The prediction and recognition of financial crisis roots have been explored [194], alongside risk management in insurance savings products [195]. Furthermore, time series forecasting and anomaly detection have been important areas of study [196]. XAI has also been used for transportation and self-driving car applications, such as the safety of self-driving cars [197], marine autonomous surface vehicle engineering [198], autonomous vehicles for object detection and networking [199, 200], and the development of advanced driver-assistance systems [201]. Similarly, XAI offered support in retail and sales, such as inventory management [202], on-shelf availability monitoring [203], predicting online purchases based on information about online behavior [204], customer journey mapping automation [205], and churn prediction [206, 207]. In the field of education, XAI has been applied to various areas such as the early prediction of student performance [208], predicting dropout rates in engineering faculties [209], forecasting alumni income [210], and analyzing student agency [211]. In psychology, XAI was used for classifying psychological traits from digital footprints [212]; in social care, for child welfare screening [213]; and in the laws, for detecting reasons behind a judge's decision-making process [214], predicting withdrawal from the legal process in cases of violence towards women in intimate relationships [215], and inter parties institution outcomes predictions [216]. In natural language processing, XAI was used for explaining sentence embedding [217], question classification [218], questions answering [219], sarcasm detection in dialogues [220], identifying emotions from speech [221], assessment of familiarity ratings for domain concepts [222], and detecting AI-generated text [223]. In entertainment, XAI was used, for example, for movie recommendations [224], explaining art [225], and different gaming applications, including analyzing and optimizing the performance of agents in a game [226], deep Q-learning experience replay [227], and cheating detection and player churn prediction [228]. Furthermore, several studies concentrated on (social) media deceptive online content (such as fake news and deepfake images) detection [229, 230, 231, 232, 233, 234]. In summary, the recent applications of XAI span a diverse array of domains, reflecting its evolving scope; Figure 4 illustrates eight notable application areas. Figure 4: Saliency maps of eight diverse recent XAI applications from various domains: brain tumor classification [116], grape leaf disease identification [144], emotion detection [235], ripe status recognition [141], volcanic localizations [236], traffic sign classification [237], cell segmentation [238], and glaucoma diagnosis [77] (from top to bottom and left to right).