Integrative Bayesian Models Using Post-Selective Inference: A Case Study in Radiogenomics is a research paper published in Biometrics (2022). On theSindex it has a DataRank of 0. It has been cited 9 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.
We only score data papers we can read in full — never from an abstract alone.
Division of Cancer Prevention, National Cancer Institute
Grant: R37CA214955-01A1
NIH
Grant: R01-CA160736
NIH
Grant: R21-CA220299
NSF
Grant: 1463233
Collaborative Research: New Bayesian Nonparametric Paradigms of Personalized Medicine for Lung Cancer
NSF
Grant: 1951980
FRG: Collaborative Research: Quantile-Based Modeling for Large-Scale Heterogeneous Data
NSF
Grant: 2113342
Reusing Data Efficiently for Iterative and Integrative Inference
CCSG
Grant: P30 CA046592
Division of Cancer Prevention, National Cancer Institute
Grant: R37CA214955‐01A1
National Institutes of Health
Grant: R01‐CA160736
National Institutes of Health
Grant: R21‐CA220299
NCI NIH HHS
Grant: R37 CA214955
NCI NIH HHS
Grant: R01 CA160736
NCI NIH HHS
Grant: R21 CA220299
NCI NIH HHS
Grant: R01 CA244845
NCI NIH HHS
Grant: R01 CA194391
National Institutes of Health
Grant: 3P30CA046592-31S7
Cancer Center Support Grant 2018-2023
FWCI
1.04
Citation Percentile
0.7%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals