ReviewInternational journal of telemedicine and applications2026
Application of Digital Twin Technology to Enhance Chronic Diseases Management: A Systematic Review.
Review in International journal of telemedicine and applications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Application of Digital Twin Technology to Enhance Chronic Diseases Management: A Systematic Review.International journal of telemedicine and applications · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Given that chronic diseases account for a considerable proportion of preventable deaths globally, the adoption of innovative technologies for disease management and prevention is crucial. Digital twins (DTs), representing one of the most advanced technological solutions, enable real-time simulation and monitoring of chronic disease progression, facilitating personalized treatment strategies and early intervention. This systematic review examines current research on DT applications in chronic disease management to evaluate their potential impact. Methods: A systematic search was conducted in four databases including PubMed, Scopus, Web of Science, and IEEE from inception to the date of the last search. The research question was formulated using PICO framework. Next, all articles were screened following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to select eligible articles based on inclusion criteria. The extracted information was analyzed to determine the main applications, domains, and employed technologies using quantitative and qualitative techniques. Results: Out of 298 citations, 20 studies met our inclusion criteria after duplicate removal and screening. Most studies (45%, Conclusions: Our findings demonstrate that DT technology has evolved from theoretical models to integrated clinical applications, with the potential to revolutionize healthcare through personalized medicine, continuous monitoring, and AI-driven decision support.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.