ArticleNPJ digital medicine2025
A scoping review of human digital twins in healthcare applications and usage patterns.
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 30 papers.
What it found
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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.
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Who cites it
30 citing papers in PubMed.
- Microbiome-based therapeutics forGut microbes · 2026Review
- Quantitative Compression Ultrasound via a Force-Area Digital Twin for Mechanistic Assessment of Venous Thrombosis.Annals of biomedical engineering · 2026Article
- Structural requirements for intelligent clinical digital twins in feedback-driven care.npj health systems · 2026Review
- Heart Failure sub-phenotyping and in-hospital and 28-day mortality prediction based on mean arterial pressure trajectory modeling.American heart journal plus : cardiology research and practice · 2026Article
- Digital twin for neurological conditions: a systematic scoping review.Biomedical engineering letters · 2026Review
- An Interpretable, Data-Driven, Hierarchical Multi-Domain Fusion Framework for Classification and Motor Function Scoring in Chronic Ankle Instability.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Artificial Intelligence and Multi-Omics Approaches in the Precision Management of Pulmonary Hypertension: From Early Diagnosis to Therapeutic Stratification.International journal of molecular sciences · 2026Review
- Digital twin-enabled robotic surgery: a bibliometric and knowledge-mapping analysis from patient-specific simulation to autonomy and clinical translation.Journal of robotic surgery · 2026Review
- Healthcare Digital Twins Across Scales: A Narrative Review and Five-Level Conceptual Framework.Healthcare (Basel, Switzerland) · 2026Review
- Timesynth: A Temporal Fidelity Framework for Health Signal Digital Twins.Research square · 2026Article
- Digital Twins as the Implementation Layer of Precision Medicine in Pediatric Neurosurgery.Journal of Korean Neurosurgical Society · 2026Review
- Mapping the role of artificial intelligence in health-related stigma: a scoping review.NPJ digital medicine · 2026Article
- Digital Twins in Orthopedics and Trauma: Concepts, Emerging Evidence, and Barriers to Clinical Translation.Journal of clinical medicine · 2026Review
- Real-time AI-Driven cadence optimization in elite 800-m runners: a bioenergetic digital twin approach under metabolic constraints.BMC sports science, medicine & rehabilitation · 2026Article
- Reply to letter to the editor on "Forecasting Anesthetic Depth Using Auto-Regressive Transformer in Propofol Infusion during Induction Phase".Journal of anesthesia · 2026Article
- Perception-first digital twin for augmented reality microsurgery.International journal of computer assisted radiology and surgery · 2026Article
- Optimized explainable AI and digital twin for patient flow improvement in ICU during respiratory epidemics.BMC medical informatics and decision making · 2026Article
- Comparative Molecular Insights and Computational Modeling of Multiple Myeloma and Osteosarcoma.International journal of molecular sciences · 2026Review
- On the accuracy of implicit neural representations for cardiovascular anatomies and hemodynamic fields.Computers in biology and medicine · 2026Article
- Clinical Artificial Intelligence Agents in Nephrology: From Prediction to Action Through Workflow-Native Intelligence-A Roadmap for Workflow-Integrated Care.Journal of clinical medicine · 2026Review
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital twins have become increasingly popular across various industries as dynamic virtual models of physical systems. In healthcare, Human Digital Twins (HDTs) serve as virtual counterparts to patients. According to the National Academies of Sciences, Engineering, and Medicine (NASEM), a digital twin must be personalized, dynamically updated, and have predictive capabilities to-in the context of health care-inform clinical decision-making. This scoping review aims to assess the current state of HDTs in healthcare, examining whether the literature aligns with the NASEM definition and identifying trends. A systematic literature search was conducted, covering articles published from January 2017 to July 2024. Only 18 of the 149 included studies (12.08%) fully met the NASEM digital twin criteria. Digital shadows made up 9.4% of studies, general digital models comprised 10.07%, and virtual patient cohorts were another 10.07%. Only two studies mentioned verification, validation, and uncertainty quantification (VVUQ), a critical NASEM standard for model reliability.
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.