Interpretable Artificial Intelligence for COVID-19 Diagnosis from Chest CT Reveals Specificity of Ground-Glass Opacities is a dataset published in medRxiv (2020). On theSindex it has a DataRank of 1.3, placing it in the top 16.3% of the data-sharing corpus. It has been cited 24 times, with 23 citing works in its 1-hop citation network.
Ranks in the top 16% 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
0.483
From this paper's citation signal
Citation Network Contribution
0.784
From 19 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 23 citers.
National Institutes of Health
Grant: 5R01MH122370-03
SCH: INT: Computational Tools for Avoidaint/Restrictive Food Intake Disorder
National Science Foundation
Grant: 1712867
CIF: AF: Small: Foundations of Multimodal Information Integration
Fields of Study
Sustainable Development Goals