Bayesian inference for fitting cardiac models to experiments: estimating parameter distributions using Hamiltonian Monte Carlo and approximate Bayesian computation is a research paper published in Medical & Biological Engineering & Computing (2022). On theSindex it has a DataRank of 0.269. It has been cited 5 times.
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Base Score Contribution
0.269
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →National Science Foundation
Grant: CNS-2028677
National Science Foundation
Grant: CMMI-1762553
National Institutes of Health
Grant: 1R01HL143450
National Science Foundation
Grant: 1762553
Collaborative Research: Developing a Quantitative Three-Dimensional Understanding of Cardiac Arrhythmias
National Institutes of Health
Grant: 5R01HL143450-06
Integrative High-Resolution Experimental and Multiscale Modeling of Arrhythmias to Optimize Low Energy Anti-fibrillation Pacing (LEAP)
National Science Foundation
Grant: 2028677
CPS: Frontier: Collaborative Research: Compositional, Approximate, and Quantitative Reasoning for Medical Cyber-Physical Systems
NHLBI NIH HHS
Grant: R01 HL143450
FWCI
1.10
Citation Percentile
0.8%
Citation Trend
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