Multimodal deep learning improves recurrence risk prediction in pediatric low-grade gliomas is a research paper published in Neuro-Oncology (2024). On theSindex it has a DataRank of 0.515. It has been cited 30 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?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
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Base Score Contribution
0.515
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: U24CA194354, K08DE030216
National Cancer Institute
Grant: 2P50CA165962
NCI NIH HHS
Grant: U54 CA274516
NCI NIH HHS
Grant: P50 CA165962
NCI NIH HHS
Grant: U24 CA194354
NIDCR NIH HHS
Grant: K08 DE030216
FWCI
8.84
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals