Two Decades of Research in Artificial Pancreas: Insights from a Bibliometric Analysis

Abstract

Background: Artificial pancreas is a well-known research topic devoted to achieving better glycemic outcomes that has been attracting increasing attention over the years. However, there is a lack of systematic, chronological, and synthesizing studies that show the background of the knowledge generation in this field. This study implements a bibliometric analysis to recognize the main documents, type of publications, research categories, countries, keywords, organizations, and authors related to this topic. Methods: Web of Science core collection database was accessed from 2000 to 2020 in order to select high-quality scientific documents based on a specific search query. Bibexcel, MS Excel, Power BI, R-Studio, VOSviewer, and CorText software were used for a descriptive and network analysis based on the local database obtained. Bibliometric parameters as the h-index, frequencies, co-authorship and co-ocurrences were computed. Results: A total of 756 documents were included that show a growing scientific production on this topic with an increasing contribution from engineering. Outstanding authors, organizations, and countries were identified. An analysis of trends in research was conducted according to the scientific categories of the Web of Science database to identify the main research interests of the last 2 decades and the emerging areas with greater prominence in the coming years. A keyword network analysis allowed to identify the main stages in the development of the AP research over time. Conclusions: Results reveal a comprehensive background of the knowledge generation for the AP topic during the last 2 decades, which has been strengthened with international collaborations and a remarkable interdisciplinarity between endocrinology and engineering, giving rise to a growing number of research areas over time, where computer science and medical informatics stand out as the main emerging research areas.

Centella asiatica (L.) Urb: A comprehensive bibliometric analysis of published studies between 1857 and 2022

“…The most cited papers are thought to be of scientific merit, high performance, and useful for benchmarking research performance in a specific area, with a high number of citations per article (36). "Chemical, pharmacological and clinical profile of the East Asian medical plant Centella asiatica" was the most cited paper which ap- *A higher total link strength/number of documents indicates more international research collaboration in a given country (35).…”

A half-century of research on microalgae-bacteria for wastewater treatment

“…The input data to perform bibliometric analysis in scientific fields is typically provided by referential databases such as Web of Science (WoS). Based on our experience [33,34], a bibliometric analysis procedure was established, which is described in this section, along with the software tools used to generate diverse bibliometric results and trends.…”

Machine Learning and Deep Learning Techniques Applied to Diabetes Research: A Bibliometric Analysis

“…In network analysis, the centrality metrics of the vertices (e.g., weighted degree, betweenness, closeness, and PageRank) are computed to provide empirical evidence of their relative importance in the network. 24 The weighted degree corresponds to the number of edge incidents in the node multiplied by the strength of each link. Betweenness centrality measures the ability of a node to carry information between groups of unconnected nodes.…”