Machine Learning Methods for Identifying Atrial Fibrillation Cases and Their Predictors in Patients With Hypertrophic Cardiomyopathy: The HCM-AF-Risk Model is a research paper published in CJC Open (2021). On theSindex it has a DataRank of 0.457. It has been cited 20 times.
Scored on demand from live citation data
Linked data & code
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.
Base Score Contribution
0.457
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 Institutes of Health
Grant: U54 GM104941
National Institutes of Health
Grant: R01 LM012527
National Science Foundation
Grant: 1650851
National Institutes of Health
Grant: 1R01LM012527-01A1
Incorporating Image-based Features into Biomedical Document Classification
National Institutes of Health
Grant: 3U54GM104941-09S1
Improving Pediatric COVID-19 Vaccine Awareness, Access, and Accountability in Underrepresented Communities
National Institutes of Health
Grant: 4U54GM104941-04
Delaware - CTR
University of California
FWCI
1.31
Citation Percentile
0.8%
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals