Digital twin prevalence in the medical caring fields: a bibliomatrics study and visualization analysis via CiteSpace

Abstract

We conducted academic research utilizing the visualization tool CiteSpace to explore the direct relationship between digital twin technology and medical care. We collected data from the Web Of Science Core Collection, PubMed ScienceDirect, SpringerLink, Wiley Online Library databases from 2010-2023, displayed visualization analysis of countries, institutions, and co-occurring keywords, cluster, citation bursts and timeline, also calculated nodes, edges, centrality, modularity and silhouette via CiteSpace 5.75r version. The data incorporated 1109 studies, graphed the yearly publication number from 2010-2023, showed a steady increase trend. The tree map displayed the top ten prominent study subjects, the first one was “Health Care Science Service”. The top three of Countries were USA, Germany and England, and the top one institution was Harvard Medical School. As for the top five keywords were “digital health”, “care”, “technology”, “digital twin”, and “telemedicine”. The rank three cluster were “Digital Health Applications”, “Digital Twin”, and “Machine Learning”. We also displayed the visualization analysis of citation bursts and timeline. Digital twins has welcomed a popular development in strong countries and top-tier institutions, and has a tight connection with mobile health and artificial intelligence. It has been widely used in clinical trials, like surgical operation and rehabilitation discipline, to predict patient treatment outcome, and estimate potential complications, we should facilitate digital twins in clinical practice conversion and application, and try to tackle the problems from privacy concern and economy challenge.