{"title":"Bibliometric analysis of artificial intelligence in healthcare research: Trends and future directions.","authors":"Renganathan Senthil, Thirunavukarasou Anand, Chaitanya Sree Somala, Konda Mani Saravanan","doi":"10.1016/j.fhj.2024.100182","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>The presence of artificial intelligence (AI) in healthcare is a powerful and game-changing force that is completely transforming the industry as a whole. Using sophisticated algorithms and data analytics, AI has unparalleled prospects for improving patient care, streamlining operational efficiency, and fostering innovation across the healthcare ecosystem. This study conducts a comprehensive bibliometric analysis of research on AI in healthcare, utilising the SCOPUS database as the primary data source.</p><p><strong>Methods: </strong>Preliminary findings from 2013 identified 153 publications on AI and healthcare. Between 2019 and 2023, the number of publications increased exponentially, indicating significant growth and development in the field. The analysis employs various bibliometric indicators to assess research production performance, science mapping techniques, and thematic mapping analysis.</p><p><strong>Results: </strong>The study reveals insights into research hotspots, thematic focus, and emerging trends in AI and healthcare research. Based on an extensive examination of the Scopus database provides a brief overview and suggests potential avenues for further investigation.</p><p><strong>Conclusion: </strong>This article provides valuable contributions to understanding the current landscape of AI in healthcare, offering insights for future research directions and informing strategic decision making in the field.</p>","PeriodicalId":73125,"journal":{"name":"Future healthcare journal","volume":"11 3","pages":"100182"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11414662/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Future healthcare journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.fhj.2024.100182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: The presence of artificial intelligence (AI) in healthcare is a powerful and game-changing force that is completely transforming the industry as a whole. Using sophisticated algorithms and data analytics, AI has unparalleled prospects for improving patient care, streamlining operational efficiency, and fostering innovation across the healthcare ecosystem. This study conducts a comprehensive bibliometric analysis of research on AI in healthcare, utilising the SCOPUS database as the primary data source.
Methods: Preliminary findings from 2013 identified 153 publications on AI and healthcare. Between 2019 and 2023, the number of publications increased exponentially, indicating significant growth and development in the field. The analysis employs various bibliometric indicators to assess research production performance, science mapping techniques, and thematic mapping analysis.
Results: The study reveals insights into research hotspots, thematic focus, and emerging trends in AI and healthcare research. Based on an extensive examination of the Scopus database provides a brief overview and suggests potential avenues for further investigation.
Conclusion: This article provides valuable contributions to understanding the current landscape of AI in healthcare, offering insights for future research directions and informing strategic decision making in the field.
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