Associating Multi-Modal Brain Imaging Phenotypes and Genetic Risk Factors via a Dirty Multi-Task Learning Method is a research paper published in IEEE Transactions on Medical Imaging (2020). On theSindex it has a DataRank of 0.574. It has been cited 45 times.
Scored on demand from live citation data
Linked data & code
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
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Base Score Contribution
0.574
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 Natural Science Foundation of China
Grant: 61973255
National Natural Science Foundation of China
Grant: 61602384
Natural Science Basic Research Program of Shaanxi
Grant: 2020JM-142
China Post-Doctoral Science Foundation
Grant: 2017M613202
Post-Doctoral Science Foundation of Shaanxi Province
Grant: 2017BSHEDZZ81
National Institutes of Health at University of Pennsylvania and Indiana University
Grant: R01 EB022574
National Institutes of Health at University of Pennsylvania and Indiana University
Grant: RF1 AG063481
National Institutes of Health at University of Pennsylvania and Indiana University
Grant: U19 AG024904
National Institutes of Health at University of Pennsylvania and Indiana University
Grant: P30 AG10133
National Institutes of Health at University of Pennsylvania and Indiana University
Grant: R01 AG19771
Alzheimer’s Disease Neuroimaging Initiative (ADNI), National Institutes of Health
Grant: U01 AG024904
DOD ADNI, Department of Defense
Grant: W81XWH-12-2-0012
NIA NIH HHS
Grant: R01 AG019771
NIA NIH HHS
Grant: P30 AG010133
NIA NIH HHS
Grant: U01 AG068057
CIHR
Fundamental Research Funds for the Central Universities at Northwestern Polytechnical University
Data Collection and Sharing for this Project
FWCI
2.98
Citation Percentile
0.9%
Citation Trend
Fields of Study
MeSH Terms
Keywords