Machine Learning-Based Prediction of COVID-19 Severity and Progression to Critical Illness Using CT Imaging and Clinical Data is a dataset published in Korean Journal of Radiology (2021). On theSindex it has a DataRank of 0.524, placing it in the top 36.9% of the data-sharing corpus. It has been cited 32 times.
Ranks in the top 37% for downstream scientific impact
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
0.524
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/National Cancer Institute R03 grant
Grant: R03CA249554
National Institutes of Health
Grant: CA223358
National Institutes of Health
Grant: DK117297
National Institutes of Health
Grant: MH120811
National Institutes of Health
Grant: EB022573
National Institutes of Health
Grant: 7K23DK120811-04
Non-Invasive Imaging Biomarkers to Identify a High-Risk Chronic Kidney Disease Phenotype
National Institutes of Health
Grant: 5R21CA223358-02
Learning radiomic signatures to early predict response of rectal cancer patients to neoadjuvant chemoradiation therapy
National Institutes of Health
Grant: 1R21DK117297-01A1
Anatomic biomarkers of chronic kidney disease progression among children
National Institutes of Health
Grant: 7R03CA249554-03
Deep learning characterization of renal tumors
FWCI
3.04
Citation Percentile
0.9%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals