Survival analysis and regression models is a research paper published in Journal of Nuclear Cardiology (2014). On theSindex it has a DataRank of 12.3. It has been cited 489 times, with 200 citing works in its 1-hop citation network.
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.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
0.929
From this paper's citation signal
Citation Network Contribution
11.3
From 200 citing papers with measurable signal
NHLBI NIH HHS
Grant: T32 HL079888
National Institutes of Health
Grant: 5T32HL079888-10
UAB Biostatistics Pre-doctoral Training Program
FWCI
20.10
Citation Percentile
1.0%
Influential Citations
13
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 1 of A novel method for interpreting survival analysis data: description and test on three major clinical trials on cardiovascular prevention
Additional file 1 of A novel method for interpreting survival analysis data: description and test on three major clinical trials on cardiovascular prevention
Additional file 2 of A novel method for interpreting survival analysis data: description and test on three major clinical trials on cardiovascular prevention
Additional file 2 of A novel method for interpreting survival analysis data: description and test on three major clinical trials on cardiovascular prevention
Additional file 3 of A novel method for interpreting survival analysis data: description and test on three major clinical trials on cardiovascular prevention
Additional file 3 of A novel method for interpreting survival analysis data: description and test on three major clinical trials on cardiovascular prevention
Additional file 2 of Prognostic risk assessment model and drug sensitivity analysis of colon adenocarcinoma (COAD) based on immune-related lncRNA pairs
Additional file 2 of Prognostic risk assessment model and drug sensitivity analysis of colon adenocarcinoma (COAD) based on immune-related lncRNA pairs
Additional file 3 of Prognostic risk assessment model and drug sensitivity analysis of colon adenocarcinoma (COAD) based on immune-related lncRNA pairs
Additional file 3 of Prognostic risk assessment model and drug sensitivity analysis of colon adenocarcinoma (COAD) based on immune-related lncRNA pairs
Additional file 8 of Personalized targeted therapy prescription in colorectal cancer using algorithmic analysis of RNA sequencing data
Additional file 8 of Personalized targeted therapy prescription in colorectal cancer using algorithmic analysis of RNA sequencing data
Additional file 1 of Segmentation of patients with small cell lung cancer into responders and non-responders using the optimal cross-validation technique
Additional file 1 of Segmentation of patients with small cell lung cancer into responders and non-responders using the optimal cross-validation technique
Additional file 3 of A novel natural killer-related signature to effectively predict prognosis in hepatocellular carcinoma
Additional file 3 of A novel natural killer-related signature to effectively predict prognosis in hepatocellular carcinoma
Additional file 2 of A novel natural killer-related signature to effectively predict prognosis in hepatocellular carcinoma
Additional file 2 of A novel natural killer-related signature to effectively predict prognosis in hepatocellular carcinoma
Additional file 1 of A novel natural killer-related signature to effectively predict prognosis in hepatocellular carcinoma
Additional file 1 of A novel natural killer-related signature to effectively predict prognosis in hepatocellular carcinoma