GEO DataSets

(Submitter supplied) Diabetic kidney disease is the leading cause of end-stage kidney disease worldwide; however, the integration of high-dimensional trans-omics data to predict this diabetic complication is rare. We develop artificial intelligence (AI)-assisted models using machine learning algorithms to identify a biomarker signature that predisposes high risk patients with diabetes mellitus (DM) to diabetic kidney disease based on clinical information, untargeted metabolomics, targeted lipidomics and genome-wide single nucleotide polymorphism (SNP) datasets. more...

Organism:

Homo sapiens

Type:

Genome variation profiling by array; SNP genotyping by SNP array

Platform:

GPL32738

616 Samples

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