Embedding high-dimensional Bayesian optimization via generative modeling: Parameter personalization of cardiac electrophysiological models is a research paper published in Medical Image Analysis (2020). On theSindex it has a DataRank of 0. It has been cited 24 times.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
NHLBI NIH HHS
Grant: R01 HL142496
National Science Foundation
Grant: ACI-1350374
NHLBI NIH HHS
Grant: R01 HL126802
NHLBI NIH HHS
Grant: R01 HL145590
National Institutes of Health
Grant: 2R01HL145590-06A1
Elucidating 3D Constructs of Reentrant Circuits via a Novel Noninvasive Hybrid-AI System
National Institutes of Health
Grant: 5R01HL142496-04
Infarct-related Ventricular Tachycardia Mechanisms: From Micro to Clinical
National Science Foundation
Grant: 1350374
CAREER: Integrating Physical Models into Data-Driven Inference
National Science Foundation
National Institutes of Health
FWCI
2.08
Citation Percentile
0.9%
Citation Trend
Fields of Study
MeSH Terms
Keywords