ReviewPacing and clinical electrophysiology : PACE2021
Data integration for the numerical simulation of cardiac electrophysiology.
Review in Pacing and clinical electrophysiology : PACE, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- A data-driven computational methodology for assessing ventricular ablation procedures.Biomechanics and modeling in mechanobiology · 2026Article
- Integrated multi-modal data analysis for computational modeling of healthy and location-dependent myocardial infarction conditions in porcine hearts.PLoS computational biology · 2026Article
- Article
- Computational modelling of biological systems now and then: revisiting tools and visions from the beginning of the century.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Review
- The role of computational methods in cardiovascular medicine: a narrative review.Translational pediatrics · 2024Review
- The health digital twin to tackle cardiovascular disease-a review of an emerging interdisciplinary field.NPJ digital medicine · 2022Review
- Optimization of Left Ventricle Pace Maker Location Using Echo-Based Fluid-Structure Interaction Models.Frontiers in physiology · 2022Article
- Data integration for the numerical simulation of cardiac electrophysiology.Pacing and clinical electrophysiology : PACE · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increasing availability of extensive and accurate clinical data is rapidly shaping cardiovascular care by improving the understanding of physiological and pathological mechanisms of the cardiovascular system and opening new frontiers in designing therapies and interventions. In this direction, mathematical and numerical models provide a complementary relevant tool, able not only to reproduce patient-specific clinical indicators but also to predict and explore unseen scenarios. With this goal, clinical data are processed and provided as inputs to the mathematical model, which quantitatively describes the physical processes that occur in the cardiac tissue. In this paper, the process of integration of clinical data and mathematical models is discussed. Some challenges and contributions in the field of cardiac electrophysiology are reported.
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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.