Three-dimensional MRI Bone Models of the Glenohumeral Joint Using Deep Learning: Evaluation of Normal Anatomy and Glenoid Bone Loss is a dataset published in Radiology Artificial Intelligence (2020). On theSindex it has a DataRank of 1.4, placing it in the top 14.9% of the data-sharing corpus. It has been cited 33 times, with 31 citing works in its 1-hop citation network.
Ranks in the top 15% 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
0.529
From this paper's citation signal
Citation Network Contribution
0.861
From 23 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 31 citers.
NIBIB NIH HHS
Grant: P41 EB017183
NIAMS NIH HHS
Grant: R01 AR072614
National Institutes of Health
Grant: 5R01AR072614-05
Prediction of Recurrent Anterior Shoulder Instability Using the On/Off Track Method and 3D MRI: A Clinical Outcomes and Cost-Effectiveness Study
National Institutes of Health
Fields of Study