ReviewPatterns (New York, N.Y.)2024
Concepts and applications of digital twins in healthcare and medicine.
Review in Patterns (New York, N.Y.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 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
64 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Digital Twins in Neuro-Oncology: A Systematic Review of Current Implementations, Technical Strategies, and Clinical Applications.Radiology. Imaging cancer · 2026Pooled it
- Clinical trials in a dish: cardiometabolic drug development with biological and digital twins.The Journal of clinical investigation · 2026Review
- Precision Prevention for Health: The Global Alliance Framework for the Promotion of Physical Activity.Sports medicine (Auckland, N.Z.) · 2026Article
- Beyond Traditional Risk Scores: Artificial Intelligence in Coronary Plaque Characterization and Personalized Atherosclerosis Management.Journal of cardiovascular development and disease · 2026Review
- A global digital navigator of human health for precision medicine.Nature medicine · 2026Article
- Prediction of maternal and infant outcomes from longitudinal electronic health records with a mother-child AI agent.Nature medicine · 2026Article
- From Intelligent Operating Room to Smart ICU: Digital Continuity, AI-Supported Decision-Making and CRRT as a Model of Pharmacokinetic Personalization in Critical Care.Healthcare (Basel, Switzerland) · 2026Review
- Structural requirements for intelligent clinical digital twins in feedback-driven care.npj health systems · 2026Review
- Longitudinal alignments and syntheses of multimodal clinical data for personalized medicine with the PULSE framework.Nature computational science · 2026Article
- Healthcare Digital Twins Across Scales: A Narrative Review and Five-Level Conceptual Framework.Healthcare (Basel, Switzerland) · 2026Review
- Digital twins for non-invasive tumor localization in breast-conserving surgery: a technical pilot study.Breast (Edinburgh, Scotland) · 2026Article
- Validating medical digital twins for clinical decision support: beyond predictive accuracy.JAMIA open · 2026Review
- From Therapeutic Drug to Xenobiotic in Cancer Repurposing: Clozapine Mechanisms, Metabolic Liabilities, and Human-Relevant Translational Approaches.Journal of xenobiotics · 2026Review
- Advancing AI for multi-omics and clinical data integration in basic and translational cancer research.Nature reviews. Cancer · 2026Review
- The Programmable Microbiome: Integrative AI and Multi-Omics Frameworks for Precision T2DM Management.Biology · 2026Review
- Digital Twins in Orthopedics and Trauma: Concepts, Emerging Evidence, and Barriers to Clinical Translation.Journal of clinical medicine · 2026Review
- Digital twins and digital models of the human circulatory system.Nature reviews bioengineering · 2026Article
- Modeling Diabetes Risk and Progression With Public Health Data: Ontology-Guided, Simulation-Capable Digital Twin Study.JMIR medical informatics · 2026Article
- Advances in nanotechnology for the diagnosis and management of autoimmune diseases.Asian journal of pharmaceutical sciences · 2026Review
- Digital Twin Technology In Radiology.Journal of imaging informatics in medicine · 2026Review
4 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The digital twin (DT) is a concept widely used in industry to create digital replicas of physical objects or systems. The dynamic, bi-directional link between the physical entity and its digital counterpart enables a real-time update of the digital entity. It can predict perturbations related to the physical object's function. The obvious applications of DTs in healthcare and medicine are extremely attractive prospects that have the potential to revolutionize patient diagnosis and treatment. However, challenges including technical obstacles, biological heterogeneity, and ethical considerations make it difficult to achieve the desired goal. Advances in multi-modal deep learning methods, embodied AI agents, and the metaverse may mitigate some difficulties. Here, we discuss the basic concepts underlying DTs, the requirements for implementing DTs in medicine, and their current and potential healthcare uses. We also provide our perspective on five hallmarks for a healthcare DT system to advance research in this field.
Identifiers
What Socratic 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 Socratic graph.