Development and validation of a model for predicting incident type 2 diabetes using quantitative clinical data and a Bayesian logistic model: A nationwide cohort and modeling study is a research paper published in PLoS Medicine (2020). On theSindex it has a DataRank of 0. It has been cited 43 times.
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.
National Institute of Neurological Disorders and Stroke
Grant: NS041588
National Institute of Diabetes and Digestive and Kidney Diseases
Grant: DK062710
American Heart Association
Grant: 17SFRN33610070
Merit Review Program
Grant: I01CX000432
UAB Diabetes Research Center
Grant: P30 DK079626
National Institute of Diabetes and Digestive and Kidney Diseases
Grant: DK056336
NIDDK NIH HHS
Grant: P30 DK056336
NINDS NIH HHS
Grant: RF1 NS041588
NINDS NIH HHS
Grant: R01 NS041588
NINDS NIH HHS
Grant: U01 NS041588
NIDDK NIH HHS
Grant: T32 DK062710
MeSH Terms
Additional file 1 of Understanding the risk of developing weight-related complications associated with different body mass index categories: a systematic review
Additional file 1 of Understanding the risk of developing weight-related complications associated with different body mass index categories: a systematic review