[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117748-en":3,"doc-seo-117748-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},117748,1099513958607,"Jiven","https://ap-avatar.wpscdn.com/avatar/100002390cf8733938c?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778829742770036399",8,"Research & Report","Machine Learning in Safety and Health Research - A Scientometric Analysis","Safety and health are interwoven and essential to business performance and human well-being, encompassing employees’ physical, emotional, and mental health. Using Scopus and Web of Science, the study examines global research output on machine learning in safety and health, including publication growth, research communication patterns by source titles, international collaborations, and author keyword trends. ScientoPy and VOSviewer support analysis, revealing Web of Science publication evolution and highlighting leading journals and countries. Findings indicate dominant institutional output and trending keywords, while suggesting scoping or systematic reviews to clarify relationships.","International Journal of Information Science and Management Vol. 21, No. 1, 2023, 17-35  \nDOI: 10.22034/ijism.2022.1977763.0 / [https://dorl.net/dor/20.1001.1.20088302.2023.21.1.2.2](https://dorl.net/dor/20.1001.1.20088302.2023.21.1.2.2)  \nOriginal Research  \nMachine Learning in Safety and Health Research: A Scientometric Analysis  \nKhairul Hafezad Abdullah  \nSenior Science Officer, Universiti Teknologi MARA, Perlis Branch, Perlis, Malaysia.  \nCorresponding Author: [ezadneo88@gmail.com](ezadneo88@gmail.com)  \nORCID iD: [https://orcid.org/0000-0003-3759-6541](https://orcid.org/0000-0003-3759-6541)  \nDavi Sofyan  \nLecturer, Department of Physical Education, Universitas Majalengka, West Java, Indonesia.  \n[davisofyan@unma.ac.id](davisofyan@unma.ac.id)  \nORCID iD: [https://orcid.org/0000-0001-9510-7123](https://orcid.org/0000-0001-9510-7123)  \nReceived: 22 March 2022  \nAccepted: 20 April 2022  \nAbstract  \nSafety 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 keywordsin 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.  \nKeywords: Machine Learning, Safety, Health, Scientometric, Scopus, Web of Science, Publication Trajectories.  \nIntroduction  \nBased on an anthropological standpoint, safety and health in any business are becoming an apparent priority increasingly. One strength of the interpretive approach relevant to this context is that the researcher provides an account of other people’s beliefs and actions; the exercise is effectuated with the consideration that the interpretation is motivated by historical and cultural causes (Sachs,1990) . Safety specialists agree that organizations’ emphasis on wellness extends  \nto employee safety in and out of the business operations; it’s about ensuring employees’physical, emotional, and mental well-being (Abdullah, Hashim & Abd Aziz, 2020; Van Nunen, Li, Reniers & Ponnet, 2018) . Likewise, managing safety and health in organizations relies heavily on preventing accidents, illnesses, and diseases (Abdullah & Abd Aziz, 2020) . It is vital since managing safety and health has become an integral part of business o","cbCailpe12dflpyb","https://ap.wps.com/l/cbCailpe12dflpyb","pdf",858902,1,19,"English","en",105,"# Introduction\n## Safety and health priorities in organizations\n## Safety-leading indicators and challenges\n## Role of artificial intelligence and machine learning\n# Abstract\n## Research aim and data sources\n## Methods and analytical tools\n## Key findings and implications","[{\"question\":\"What data sources and tools are used to analyze machine learning research in safety and health?\",\"answer\":\"The study uses Scopus and Web of Science as data sources. It applies ScientoPy and VOSviewer to analyze publication growth, communication patterns, collaborations, and keyword trends.\"},{\"question\":\"Which database tracks the evolution of publications over time, and which source title leads in publishing activity?\",\"answer\":\"The study states that Web of Science tracks the evolution of publications throughout time. It also reports that PLoS One surpasses other source titles in publishing activity.\"},{\"question\":\"What do the keyword trends from 2020 to 2021 suggest for the field?\",\"answer\":\"The keywords “machine learning”, “artificial intelligence”, “electronic health records”, “deep learning”, and “mental health” are described as the most popular and trending in 2020 and 2021. “Artificial intelligence” appears in most publications.\"}]","Machine Learning in Safety and Health Research - A Scientometric Analysis | PDF",1785679332,48,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-in-safety-and-health-research-a-scientometric-analysis","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-in-safety-and-health-research-a-scientometric-analysis/117748/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What data sources and tools are used to analyze machine learning research in safety and health?","Question",{"text":75,"@type":76},"The study uses Scopus and Web of Science as data sources. 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