Automated Lung Cancer Segmentation Using a PET and CT Dual-Modality Deep Learning Neural Network is a research paper published in International Journal of Radiation Oncology*Biology*Physics (2022). On theSindex it has a DataRank of 0.500. It has been cited 27 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
0.500
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: P30CA016059
National Institutes of Health
Grant: U01 AI133595
FWCI
4.74
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 1 of 18F-FDG-PET/CT-based deep learning model for fully automated prediction of pathological grading for pancreatic ductal adenocarcinoma before surgery
Additional file 1 of 18F-FDG-PET/CT-based deep learning model for fully automated prediction of pathological grading for pancreatic ductal adenocarcinoma before surgery