Digital twins in precision medicine provide tailored health recommendations by simulating patient-specific trajectories and interventions. We examine the critical role of Verification, Validation, and Uncertainty Quantification (VVUQ) for digital twins in ensuring safety and efficacy, with examples in cardiology and oncology. We highlight challenges and opportunities for developing personalized trial methodologies, validation metrics, and standardizing VVUQ processes. VVUQ frameworks are essential for integrating digital twins into clinical practice.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11742391 | PMC |
| http://dx.doi.org/10.1038/s41746-025-01447-y | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Profiling microRNA expression differentiates monozygotic twins in peripherical blood by droplet digital PCR.
Forensic Sci Int Genet
January 2025
School of Forensic Medicine, China Medical University, Shenyang 110000, PR China; Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, Liaoning Province 110000, PR China; China Medical University Center of Forensic Investigation, Shenyang 110000, PR China. Electronic address:
It is challenging to distinguish monozygotic (MZ) twins using traditional autosomal STR genotyping due to their nearly identical genomes. As an important kind of small non-coding RNAs, microRNAs (miRNAs) are essential regulators of gene expression and considered as excellent biomarkers due to their resistance to degradation. Moreover, droplet digital PCR (ddPCR) has emerged as a powerful technique for detecting gene mutations and pathogenic microorganisms, owing to its sensitivity and reliability.
View Article and Find Full Text PDFProbabilistic learning of the Purkinje network from the electrocardiogram.
Med Image Anal
January 2025
Department of Mechanical and Metallurgical Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile; Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile; Millennium Institute for Intelligent Healthcare Engineering, iHEALTH, Chile. Electronic address:
The identification of the Purkinje conduction system in the heart is a challenging task, yet essential for a correct definition of cardiac digital twins for precision cardiology. Here, we propose a probabilistic approach for identifying the Purkinje network from non-invasive clinical data such as the standard electrocardiogram (ECG). We use cardiac imaging to build an anatomically accurate model of the ventricles; we algorithmically generate a rule-based Purkinje network tailored to the anatomy; we simulate physiological electrocardiograms with a fast model; we identify the geometrical and electrical parameters of the Purkinje-ECG model with Bayesian optimization and approximate Bayesian computation.
View Article and Find Full Text PDFRevolutionizing Surgical Preparedness: Personalized Preoperative Planning with Digital Twins of an Organ.
Surg Innov
January 2025
Paediatrics & Child Health, Aga Khan University Hospital, Karachi, Pakistan.
Biokinetic soft-sensing using Thiothrix and Ca. Microthrix bacteria to calibrate secondary settling, aeration and NO emission digital twins.
Water Res
January 2025
Department of Chemical Engineering, University of Bath, Claverton Down, Bath BA2 7AY, UK; SWING - Department of Built Environment, Oslo Metropolitan University, St Olavs plass 0130, Oslo, Norway. Electronic address:
Climate resilience in water resource recovery facilities (WRRFs) necessitates improved adaptation to shock-loading conditions and mitigating greenhouse gas emission. Data-driven learning methods are widely utilised in soft-sensors for decision support and process optimization due to their simplicity and high predictive accuracy. However, unlike for mechanistic models, transferring machine-learning-based insights across systems is largely infeasible, which limits communication and knowledge sharing.
View Article and Find Full Text PDFDigital Representation of Patients as Medical Digital Twins: Data-Centric Viewpoint.
JMIR Med Inform
January 2025
INSERM U1064, CR2TI - Center for Research in Transplantation and Translational Immunology, Nantes University, 30 Bd Jean Monnet, Nantes, 44093, France, 33 2 40 08 74 10.
Precision medicine involves a paradigm shift toward personalized data-driven clinical decisions. The concept of a medical "digital twin" has recently become popular to designate digital representations of patients as a support for a wide range of data science applications. However, the concept is ambiguous when it comes to practical implementations.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!