ArticleNPJ digital medicine2025
A consensus statement on the use of digital twins in medicine.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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
12 citing papers in PubMed.
- Digital Twin-Assisted Risk Disclosure in Adults Undergoing Elective Bronchoscopy: Multicenter Randomized Controlled Trial.Journal of medical Internet research · 2026Trial
- Validating medical digital twins for clinical decision support: beyond predictive accuracy.JAMIA open · 2026Review
- Narrative Review of Digital Twins in the Health Domain: Development, Application, and Evidence Consolidation.Medical sciences (Basel, Switzerland) · 2026Review
- Future-Making From Afar: Digital Twins in Medicine.Sociology of health & illness · 2026Article
- Neonatal digital twins enable personalized antibiotic dosing for treating suspected sepsis.NPJ digital medicine · 2026Article
- Digital twins of ex vivo human lungs enable accurate and personalized evaluation of therapeutic efficacy.Nature biotechnology · 2026Article
- A survey on ethical digital twins in healthcare.Frontiers in artificial intelligence · 2026Review
- Digital Twins as catalysts for Whole Person Health Mind Body Medicine in Integrative Oncology.Frontiers in oncology · 2026Article
- Digital Twins in Personalized Medicine: Bridging Innovation and Clinical Reality.Journal of personalized medicine · 2025Review
- CRISPR and Artificial Intelligence in Neuroregeneration: Closed-Loop Strategies for Precision Medicine, Spinal Cord Repair, and Adaptive Neuro-Oncology.International journal of molecular sciences · 2025Review
- Large language models for neurology: a mini review.Frontiers in digital health · 2025Review
- Digital twins in healthcare: A systematic review of current applications, frameworks, and future directions.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital Health Technologies represent a marked shift from current medical technologies in use, the approach to health and healthcare and stakeholders engaged in healthcare delivery. What the digitalized future of medicine will look like and how it should be governed is unclear. A participatory process with interdisciplinary expert groups developed scenarios of Artificial Intelligence use in medicine and recommendations on their governance. The process included a patient-consumer focus group and the recommendations were validated by a representative population survey in Switzerland. Digital twins were identified as a pivotal innovation for personalized healthcare, with 62% of the Swiss population expressing interest, though 87% oppose mandatory use. Additionally, 75% view the state as responsible for ensuring necessary infrastructure. Digital twins are seen as an opportunity to support both the healthcare provider as well as patient-consumer directly in different modes of use and along functions, prevention, diagnosis, prognosis, and therapy.
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.