Knowledge mapping and research hotspots of artificial intelligence on ICU and Anesthesia: from a global bibliometric perspective

Abstract

AbstractThe swift advancement of technology has led to the widespread utilization of artificial intelligence (AI) in the diagnosis of diseases and prediction of prognoses, particularly in the field of intensive care unit (ICU) and Anesthesia. Numerous evidential data have demonstrated the extensive potential of AI in monitoring and predicting patient outcomes in these fields. Using bibliometric analysis, this study provides an overview of the current state of knowledge regarding the application of AI in ICU and Anesthesia and investigates prospective avenues for future research. Web of Science Core Collection was queried on May 6, 2023, to select articles and reviews regarding AI in ICU and Anesthesia. Subsequently, various analytical tools including Microsoft Excel 2022, VOSviewer (version 1.6.16), Citespace (version 6.2.R2), and an online bibliometric platform were employed to examine the publication year, citations, authors, countries, institutions, journals, and keywords associated with this subject area. This study selected 2196 articles from the literature. focusing on AI-related research within the fields of ICU and Anesthesia, which has increased exponentially over the past decade. Among them, the USA ranked first with 634 publications and had close international cooperation. Harvard Medical School was the most productive institution. In terms of publications, Scientific Reports (impact factor (IF) 4.996) had the most, while Critical Care Medicine (IF 9.296) had the most citations. According to numerous references, researchers may focus on the following research hotspots: “Early Warning Scores”, “Covid-19″, “Sepsis” and “Neural Networks”. “Procalcitonin” and “Convolutional Neural Networks” were the hottest burst keywords. The potential applications of AI in the fields of ICU and Anesthesia have garnered significant attention from scholars, prompting an increase in research endeavors. In addition, it is imperative for various countries and institutions to enhance their collaborative efforts in this area. The research focus in the upcoming years will center on sepsis and coronavirus, as well as the development of predictive models utilizing neural network algorithms to improve well-being and quality of life in surviving patients. Graphical Abstract