Automatic Machine Learning to Differentiate Pediatric Posterior Fossa Tumors on Routine MR Imaging is a research paper published in American Journal of Neuroradiology (2020). On theSindex it has a DataRank of 0.637. It has been cited 69 times.
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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
0.637
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: 61702559
NCI NIH HHS
Grant: F30 CA239407
the Planned Science and Technology Project of Hunan Province, China
Grant: 2017WK2074
National Natural Science Foundation of China
Grant: 81301988
Natural Science Foundation of Hunan Province for Young Scientists, China
Grant: 2018JJ3709
National Natural Science Foundation of China
Grant: 8181101287
the 111 project
Grant: No.B18059
NIBIB NIH HHS
Grant: T32 EB001680
National Institutes of Health
Grant: 5T32EB001680-12
Neuroimaging Training Program
National Institutes of Health
Grant: 1F30CA239407-01
Automatic Volumetric Treatment Response Assessment and Determination of Regional Genetic Characteristics in Glioblastoma
FWCI
4.27
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals