SynTwin: A graph-based approach for predicting clinical outcomes using digital twins derived from synthetic patients is a research paper published in PubMed (2023). On theSindex it has a DataRank of 0.740. It has been cited 16 times, with 15 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 — 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
0.425
From this paper's citation signal
Citation Network Contribution
0.315
From 11 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 15 citers.
NIA NIH HHS
Grant: U01 AG066833
NLM NIH HHS
Grant: R01 LM010098
NIGMS NIH HHS
Grant: R35 GM131905
NIA NIH HHS
Grant: R01 AG066833
FWCI
3.54
Citation Percentile
0.9%
Influential Citations
1
Citation Trend
Fields of Study
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Keywords