On the public citation graph

Progression of chronic kidney disease in African Americans with type 2 diabetes mellitus using topology learning in electronic medical records

0 signed · 34 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/gepi.22126openalex-snapshot
Genome‐wide interaction with the insulin secretion locus MTNR1B reveals CMIP as a novel type 2 diabetes susceptibility gene in African Americans
inferredcites →https://doi.org/10.1002/widm.2openalex-snapshot
Robust statistics for outlier detection
inferredcites →https://doi.org/10.1007/s11906-011-0237-4openalex-snapshot
Target Organ Damage in African American Hypertension: Role of APOL1
inferredcites →https://doi.org/10.1007/s40565-018-0398-0openalex-snapshot
Short-term local prediction of wind speed and wind power based on singular spectrum analysis and locality-sensitive hashing
inferredcites →https://doi.org/10.1016/j.ipl.2018.03.018openalex-snapshot
Why locality sensitive hashing works: A practical perspective
inferredcites →https://doi.org/10.1016/j.kint.2018.03.017openalex-snapshot
Genome-wide association studies suggest that APOL1-environment interactions more likely trigger kidney disease in African Americans with nondiabetic nephropathy than strong APOL1–second gene interactions
inferredcites →https://doi.org/10.1016/j.patcog.2007.05.018openalex-snapshot
A survey of kernel and spectral methods for clustering
inferredcites →https://doi.org/10.1016/j.semnephrol.2016.05.005openalex-snapshot
The Role of Acute Kidney Injury in Chronic Kidney Disease
inferredcites →https://doi.org/10.1038/ki.2011.379openalex-snapshot
Chronic kidney disease after acute kidney injury: a systematic review and meta-analysis
inferredcites →https://doi.org/10.1038/ki.2011.405openalex-snapshot
Increased risk of death and de novo chronic kidney disease following reversible acute kidney injury
inferredcites →https://doi.org/10.1038/ki.2011.42openalex-snapshot
The severity of acute kidney injury predicts progression to chronic kidney disease
inferredcites →https://doi.org/10.1038/ki.2012.208openalex-snapshot
Acute kidney injury and chronic kidney disease: an integrated clinical syndrome
inferredcites →https://doi.org/10.1038/ki.2012.263openalex-snapshot
Apolipoprotein L1 gene variants associate with hypertension-attributed nephropathy and the rate of kidney function decline in African Americans
inferredcites →https://doi.org/10.1038/nmeth.4402openalex-snapshot
Reversed graph embedding resolves complex single-cell trajectories
inferredcites →https://doi.org/10.1053/j.ajkd.2016.12.004openalex-snapshot
US Renal Data System 2016 Annual Data Report: Epidemiology of Kidney Disease in the United States
inferredcites →https://doi.org/10.1053/s0272-6386(17)30647-9openalex-snapshot
Contents
inferredcites →https://doi.org/10.1056/nejmoa1310345openalex-snapshot
APOL1 Risk Variants, Race, and Progression of Chronic Kidney Disease
inferredcites →https://doi.org/10.1089/cmb.2017.0113openalex-snapshot
Shared Nearest Neighbor Clustering in a Locality Sensitive Hashing Framework
inferredcites →https://doi.org/10.1109/tpami.2004.1307293openalex-snapshot
IEEE Transactions on Pattern Analysis and Machine Intelligence
inferredcites →https://doi.org/10.1109/tpami.2016.2635657openalex-snapshot
Principal Graph and Structure Learning Based on Reversed Graph Embedding
inferredcites →https://doi.org/10.1109/tpami.2017.2785402openalex-snapshot
Probabilistic Dimensionality Reduction via Structure Learning
inferredcites →https://doi.org/10.1126/science.1193032openalex-snapshot
Association of Trypanolytic ApoL1 Variants with Kidney Disease in African Americans
inferredcites →https://doi.org/10.1146/annurev-med-050214-013407openalex-snapshot
Acute Kidney Injury
inferredcites →https://doi.org/10.1186/1471-2105-11-447openalex-snapshot
Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification algorithms
inferredcites →https://doi.org/10.1371/journal.pgen.1005352openalex-snapshot
Genome-Wide Association and Trans-ethnic Meta-Analysis for Advanced Diabetic Kidney Disease: Family Investigation of Nephropathy and Diabetes (FIND)
inferredcites →https://doi.org/10.1681/asn.2010070730openalex-snapshot
The Apolipoprotein L1 (APOL1) Gene and Nondiabetic Nephropathy in African Americans
inferredcites →https://doi.org/10.1681/asn.2015010006openalex-snapshot
Failed Tubule Recovery, AKI-CKD Transition, and Kidney Disease Progression
inferredcites →https://doi.org/10.2215/cjn.01120211openalex-snapshot
Acute Kidney Injury Episodes and Chronic Kidney Disease Risk in Diabetes Mellitus
inferredcites →https://doi.org/10.2215/cjn.06480612openalex-snapshot
Association between AKI, Recovery of Renal Function, and Long-Term Outcomes after Hospital Discharge
inferredcites →https://doi.org/10.2337/dc17-0820openalex-snapshot
FGF23 Concentration and APOL1 Genotype Are Novel Predictors of Mortality in African Americans With Type 2 Diabetes
inferredcites →https://doi.org/10.4086/toc.2012.v008a014openalex-snapshot

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-981-16-1681-5_26openalex-snapshot
Identification of Congestive Heart Failure Patients Through Natural Language Processing
inferred← citeshttps://doi.org/10.1093/jamia/ocae158openalex-snapshot
TrajVis: a visual clinical decision support system to translate artificial intelligence trajectory models in the precision management of chronic kidney disease
inferred← citeshttps://doi.org/10.1101/2023.08.13.23293968openalex-snapshot
DEPOT: graph learning delineates the roles of cancers in the progression trajectories of chronic kidney disease using electronic medical records
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.