ArticleBMC pulmonary medicine2026
Digital twins in pulmonary medicine: a scoping review of applications, benefits, and challenges.
Article in BMC pulmonary medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimDigital twins, a newly emerging technology, are increasingly used in pulmonary medicine across various aspects of prognosis, diagnosis, and therapy. Cognition and awareness of the applications, benefits, and challenges of digital twins in pulmonary medicine are paramount in shaping future efforts by healthcare stakeholders. This study aims to map the existing literature and conduct a narrative synthesis of these determinants to provide an in-depth understanding of this topic.
methodsThis scoping review was carried out in accordance with PRISMA-ScR. Web of Science, PubMed, Scopus, Google Scholar, and IEEE Xplore were searched from their inception until January 30, 2026, in conjunction with a manual search. The English papers, original research papers, and conference papers were considered. A validated data extraction form was utilized to obtain relevant data from the existing literature. The results were presented in tables, figures, descriptive statistics, and narrative synthesis.
resultsEight studies met the inclusion criteria. A total of 41 applications, 37 benefits, and 28 challenges of digital twins in pulmonary medicine were identified. Applications are primarily focused on clinical monitoring, decision support and modeling, mechanistic modeling, technical/data and AI integration, intervention simulation, and disease management.
conclusionThis review provides a comprehensive overview of the current applications, benefits, and challenges of digital twins in pulmonary medicine. Mapping the existing evidence highlights the growing role of digital twins in patient monitoring, personalized care, and clinical decision support. The findings also identify critical barriers to the development of digital twins in this field. These insights can guide researchers, clinicians, healthcare organizations, and policymakers in prioritizing future research, developing implementation strategies, and supporting the safe integration of digital twins into pulmonary care.
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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.