Algorithmic Fairness of Machine Learning Models for Alzheimer Disease Progression is a research paper published in JAMA Network Open (2023). On theSindex it has a DataRank of 1.1. It has been cited 44 times, with 44 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.
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Base Score Contribution
0.571
From this paper's citation signal
Citation Network Contribution
0.495
From 24 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 44 citers.
NIA NIH HHS
Grant: U01 AG024904
NIA NIH HHS
Grant: R21 AG075574
National Institutes of Health
Grant: 1R21AG075574-01
Informatics Methods for Leveraging Clinical Data Sources to Study Risk Factors for Alzheimer's Disease
Canadian Institutes of Health Research
Grant: unidentified
unidentified
European Commission
Grant: 666992
Data-driven models for Progression Of Neurological Disease
National Institutes of Health
Grant: 1U01AG024904-01
Alzheimers Disease Neuroimaging Initiative
CIHR
FWCI
7.97
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords