Using Quantitative Imaging for Personalized Medicine in Pancreatic Cancer: A Review of Radiomics and Deep Learning Applications is a research paper published in Cancers (2022). On theSindex it has a DataRank of 0.641. It has been cited 71 times.
Scored on demand from live citation data
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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
0.641
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: 2P50CA127297-06A1
FWCI
8.59
Citation Percentile
1.0%
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals
Additional file 1 of Preoperative prediction of early recurrence in resectable pancreatic cancer integrating clinical, radiologic, and CT radiomics features
Additional file 1 of Preoperative prediction of early recurrence in resectable pancreatic cancer integrating clinical, radiologic, and CT radiomics features