Deep learned representations of the resting 12-lead electrocardiogram to predict at peak exercise is a research paper published in European Journal of Preventive Cardiology (2023). On theSindex it has a DataRank of 0.537. It has been cited 14 times, with 11 citing works in its 1-hop citation network.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph β 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 β never from an abstract alone.
Base Score Contribution
0.406
From this paper's citation signal
Citation Network Contribution
0.131
From 5 citing papers with measurable signal
Ranked by each citer's contribution to N(p) β log1p(Cq) divided by its reference count β out of 11 citers.
NIH
Grant: K23HL169839
NIH
Grant: R01HL134893
NIH
Grant: R01HL140224
NIH
Grant: K24HL153669
NIH
Grant: 1K23HL159262-01A1
NIH
Grant: 1R01HL092577
NIH
Grant: 1R01HL157635
American Heart Association
Grant: 23CDA1050571
American Heart Association
Grant: 18SFRN34250007
American Heart Association Harold Amos Program
Grant: 19AMFDP34990046
Presidents and Fellows of Harvard College
Grant: 5KL2TR002542-04
American Heart Association Strategically Focused Research Networks
Grant: 18SFRN34110082
European Union
Grant: MAESTRIA 965286
NHLBI NIH HHS
Grant: K23 HL159262
NHLBI NIH HHS
Grant: R01 HL157635
NCATS NIH HHS
Grant: KL2 TR002542
FWCI
4.92
Citation Percentile
0.9%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals