Deep learning-based automatic tumor burden assessment of pediatric high-grade gliomas, medulloblastomas, and other leptomeningeal seeding tumors is a research paper published in Neuro-Oncology (2021). On theSindex it has a DataRank of 0.654. It has been cited 77 times.
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
0.654
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 Institutes of Health
Grant: 5T32EB1680
National Institutes of Health
Grant: F30CA239407
High-tech Industry of Hunan Province
Grant: 2020GK2021
National Institutes of Health
Grant: 1F30CA239407-01
Automatic Volumetric Treatment Response Assessment and Determination of Regional Genetic Characteristics in Glioblastoma
National Institutes of Health
Grant: 5T32EB001680-12
Neuroimaging Training Program
FWCI
6.41
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals