Automated cardiac volume assessment and cardiac long- and short-axis imaging plane prediction from electrocardiogram-gated computed tomography volumes enabled by deep learning is a research paper published in European Heart Journal - Digital Health (2021). On theSindex it has a DataRank of 0. It has been cited 22 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.
NIH
Grant: NHLBI HL145817
NIH
Grant: HL143113
NIH HHS
Grant: S10 OD010417
NHLBI NIH HHS
Grant: R25 HL145817
NHLBI NIH HHS
Grant: K01 HL143113
NHLBI NIH HHS
Grant: T32 HL007444
National Institutes of Health
Grant: 5R25HL145817-05
UCSD PRIDE Faculty Development Program in Cardiovascular Sciences
National Institutes of Health
Grant: 3K01HL143113-05S1
Comprehensive Assessment of Right Ventricular and Pulmonary Vascular Function via CT Imaging in Heart Failure Patients
National Institutes of Health
Fields of Study
Keywords
Sustainable Development Goals