Artificial Intelligence in Intensive Care Medicine: Bibliometric Analysis

作者：Ri Tang, Shuyi Zhang, Chenling Ding, Mingli Zhu, Yuan Gao · 发表于：Journal of Medical Internet Research · 年份：2022 · DOI：10.2196/42185 · 被引用次数：78 · 研究领域：Artificial Intelligence in Healthcare and Education、Sepsis Diagnosis and Treatment、COVID-19 diagnosis using AI

BACKGROUND: Interest in critical care-related artificial intelligence (AI) research is growing rapidly. However, the literature is still lacking in comprehensive bibliometric studies that measure and analyze scientific publications globally. OBJECTIVE: The objective of this study was to assess the global research trends in AI in intensive care medicine based on publication outputs, citations, coauthorships between nations, and co-occurrences of author keywords. METHODS: A total of 3619 documents published until March 2022 were retrieved from the Scopus database. After selecting the document type as articles, the titles and abstracts were checked for eligibility. In the final bibliometric study using VOSviewer, 1198 papers were included. The growth rate of publications, preferred journals, leading research countries, international collaborations, and top institutions were computed. RESULTS: The number of publications increased steeply between 2018 and 2022, accounting for 72.53% (869/1198) of all the included papers. The United States and China contributed to approximately 55.17% (661/1198) of the total publications. Of the 15 most productive institutions, 9 were among the top 100 universities worldwide. Detecting clinical deterioration, monitoring, predicting disease progression, mortality, prognosis, and classifying disease phenotypes or subtypes were some of the research hot spots for AI in patients who are critically ill. Neural networks, decision support systems, machine ...