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Safety and health are intricately interwoven and have become indispensable to the thriving business world and anthropology. It is concerned with ensuring employees' physical, emotional, and mental well-being. Based on the Scopus and Web of Science databases, the current study intends to analyse the global research output on machine learning in safety and health. This study utilized ScientoPy and VOSviewer to delve into the annual growth, patterns of research communication on source titles, international collaboration among countries, and authors' keyword analysis. This study found that the Web of Science database tracks the evolution of publications throughout time. PLoS One has surpassed all other source titles in terms of publishing activity. Also, this study indicated that US researchers are constantly working on machine learning in safety and health research and have developed significant collaborations with China and Australia. Between 2020 and 2021, the University of Toronto published 86% of all papers, outpacing other institutions. The keywords "machine learning", "artificial intelligence", "electronic health records", "deep learning", and "mental health" were the most popular and trending keywords in 2020 and 2021, and "artificial intelligence" appeared in most publications among others. Future researchers should conduct scoping or systematic literature reviews to elucidate the relationships between these terms. This study may entice the curiosity of practitioners and researchers to advance new knowledge in this field by being devoted to cutting-edge research in the contemporary philosophy of science, cognitive, and cultural anthropology on machine learning in safety and health research. In conclusion, this scientometric analysis demonstrates that machine learning in safety and health is a study domain that requires further refinement in future research, as this technology has the potential to significantly improve workplace safety and health through targeted applications with clear benefits. [ABSTRACT FROM AUTHOR]

Every single person is entitled to equal space on the roads or sidewalks, so they rely on each other's empathy and compassion and not be self-centered. Therefore, it is essential to promote the ethics of road safety and road users' exemplary behavior upmost. This review analyzed the publication trends and thematic evolution of road user behaviour over 47 years from 1973 to 2020. The assessment uses the Scopus database and various bibliometric indicators, such as output growth trends, eminent countries, research hotspots, and author keywords. Also, this study presented a graphical visualization of bibliometric indicators using a VOSviewer. Another bibliometric software tool, known as SciMAT, was used to inspect road user behaviour research's thematic evolution. The verdicts revealed that the number of publications increased exponentially, starting in 2005 with a hike in publications in 2020. Road user behaviour researches were diverse by examining the various research hotspots. This review also focuses on several themes and dimensions of road user behaviour research. The essential motor theme during the first period (2005-2012) was "schools". Other motor themes, such as "cross-sectional studies," "car", and "space-temporal-analysis", became the most significant number of publications in the second period (2013-2020). These four themes may be beneficial as a benchmark for researchers focusing on the art of road user behaviour. This bibliometric study provides a comprehensive and in-depth view of road users' behaviour that may help future researchers advance potential knowledge in this field. [ABSTRACT FROM AUTHOR]