Tumor Connectomics: Mapping the Intra-Tumoral Complex Interaction Network Using Machine Learning is a research paper published in Cancers (2022). On theSindex it has a DataRank of 0.241. It has been cited 4 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
0.241
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: 5P30CA006973 (Imaging Response Assessment Team-IRAT)
National Institutes of Health
Grant: U01CA140204
National Institutes of Health
Grant: 1R01CA190299
National Institutes of Health
Grant: R01CA18144
National Institutes of Health
Grant: R01CA249882
The State of Wisconsin
Grant: Tax Check-off Program for Prostate Cancer Research
NCI NIH HHS
Grant: R01 CA218144
National Institutes of Health
Grant: 5R01CA190299-07
Correction of Diffusion Gradient Bias in Quantitative Diffusivity Metrics for MultiPlatform Clinical Oncology Trials
National Institutes of Health
Grant: 3P30CA006973-53S2
Regional Oncology Research Center
National Institutes of Health
Grant: 5U01CA140204-03
Multi-Modality Quantitiative Imaging for Evaluation of Response to Cancer Therapy
National Institutes of Health
Grant: 5R01CA249882-04
Prostate Cancer Radio-Pathomics for Differentiating Clinically Significant Disease
FWCI
0.39
Citation Percentile
0.6%
Influential Citations
1
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals
Data from LGG-1p19qDeletion