ReviewFrontiers in digital health2025
Digital twin for personalized medicine development.
Review in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Blockchain-enabled digital twin systems in healthcare: a systematic scoping review of architectural integration, privacy, governance, ethical challenges, and regulatory solutions under GDPR and HIPAA.Frontiers in digital health · 2026Pooled it
- Digital Twins for Hospital and Healthcare Operations: A Systematic Review of Resource Allocation, Infection Control, and Workflow Optimization.Bioengineering (Basel, Switzerland) · 2026Review
- Toward Precision Oral Medicine in Pemphigus Vulgaris: A Conceptual AI Framework for Rituximab Response Prediction.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Leveraging Advanced AI Frameworks for Dual PPAR α/γ Agonist Discovery in Alzheimer's Disease.ACS chemical neuroscience · 2026Review
- A decade of innovation in healthcare: Automation, bio-printing and digital twin technologies for personalized therapies.International journal of pharmaceutics: X · 2026Review
- Digital Twins in Orthopedics and Trauma: Concepts, Emerging Evidence, and Barriers to Clinical Translation.Journal of clinical medicine · 2026Review
- An Integrative Review of the Cardiovascular Disease Spectrum: Integrating Multi-Omics and Artificial Intelligence for Precision Cardiology.Diseases (Basel, Switzerland) · 2026Review
- A survey on ethical digital twins in healthcare.Frontiers in artificial intelligence · 2026Review
- An intelligent digital twin framework with AI-driven optimization for patient flow and clinical scheduling in smart healthcare systems.Frontiers in digital health · 2026Article
- SOMA: a preventive health governance framework for adaptive, consumer-facing digital health guidance.Frontiers in digital health · 2026Article
- Towards precision medicine in Tourette syndrome: a perspective on AI-driven predictive modelling and personalised care.Frontiers in computational neuroscience · 2026Review
- Active Rehabilitation Technologies for Post-Stroke Patients.Biosensors · 2025Review
- Designing Neural Dynamics: From Digital Twin Modeling to Regeneration.International journal of molecular sciences · 2025Review
- Time Series Models of the Human Heart in Patients with Heart Failure: Toward a Digital Twin Approach.Sensors (Basel, Switzerland) · 2025Article
- The Endocannabinoid-Microbiota-Neuroimmune Super-System: A Unifying Feedback Architecture for Systems Resilience, Collapse Trajectories, and Precision Feedback Medicine.International journal of molecular sciences · 2025Review
- Toward a Digital Twin of the Female Pelvic Floor.EC gynaecology · 2025Article
- Acoustic immune reprogramming: a novel paradigm for spatiotemporally controlled immune regulation using ultrasound-responsive nanoplatforms.Frontiers in immunology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital Twin (DT) technology is revolutionizing healthcare by enabling real-time monitoring, predictive analytics, and highly personalized medical care. As a key innovation of Industry 4.0, DTs integrate advanced tools like artificial intelligence (AI), the Internet of Things (IoT), and machine learning (ML) to create dynamic, data-driven replicas of patients. These digital replicas allow simulations of disease progression, optimize diagnostics, and personalize treatment plans based on individual genetic and lifestyle profiles. This review explores the evolution, architecture, and enabling technologies of DTs, focusing on their transformative applications in personalized medicine (PM). While the integration of DTs offers immense potential to improve outcomes and efficiency in healthcare, challenges such as data privacy, system interoperability, and ethical concerns must be addressed. The paper concludes by highlighting future directions, where AI, cloud computing, and blockchain are expected to play a pivotal role in overcoming these limitations and advancing precision medicine.
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.