This study aims to provide a comprehensive overview of research on digital medicine in cardiovascular diseases (CVD), exploring its evolution, knowledge framework, and current research hotspots, and offering insights for future investigations in this field. Publications from January 2004 to October 2022 were collected from the Web of Science Core Collection (WoSCC). CiteSpace was utilized to visualize keyword trends, co-citation networks, and emerging research frontiers, while VOSviewer mapped the contributions of authors, institutions, and countries, integrating their link strengths into the analysis.
A total of 5,265 English-language articles were included. Publication output has steadily grown each year. The United States led in the number of publications, followed by England. Harvard Medical School was the most prolific institution, with Massachusetts General Hospital and Brigham and Women’s Hospital also ranking highly. The journal JMIR mHealth and uHealth was the most influential outlet. Among authors, Noseworthy PA stood out for both citation counts and total link strength. The application of wearable devices in CVD—covering risk identification, diagnosis, preventive strategies, early intervention, and remote management—emerges as a foundational and highly explored area. Future research directions may include evaluating the clinical impact of digital interventions on chronic disease management, applying machine learning (ML) for atrial fibrillation (AF) detection and early risk assessment, and developing predictive models for CVD outcomes using neural networks (NNs), ML, and unsupervised learning approaches. Research on digital medicine in CVD has grown markedly in recent years. This bibliometric study presents a detailed map of the field, serving as a reference for researchers aiming to advance knowledge and practice in this area.
