{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"submitter":["Lucarelli N"],"pubmed_abstract":["<h4>Background</h4>The heterogeneous phenotype of diabetic nephropathy (DN) from type 2 diabetes complicates appropriate treatment approaches and outcome prediction. Kidney histology helps diagnose DN and predict its outcomes, and an artificial intelligence (AI)-based approach will maximize clinical utility of histopathological evaluation. Herein, we addressed whether AI-based integration of urine proteomics and image features improves DN classification and its outcome prediction, altogether augmenting and advancing pathology practice.<h4>Methods</h4>We studied whole slide images (WSIs) of periodic acid-Schiff-stained kidney biopsies from 56 DN patients with associated urinary proteomics data. We identified urinary proteins differentially expressed in patients who developed end-stage kidne"],"journal":["medRxiv : the preprint server for health sciences"],"pagination":["2023.04.28.23289272"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10187347"],"repository":["biostudies-literature"],"pubmed_title":["Discovery of Novel Digital Biomarkers for Type 2 Diabetic Nephropathy Classification via Integration of Urinary Proteomics and Pathology."],"pmcid":["PMC10187347"],"pubmed_authors":["Rosenberg AZ","Jen KY","Zee J","Yun D","Sarder P","Tomaszewski JE","Han D","Han SS","Lucarelli N","Ginley B","Moon KC"],"additional_accession":[]},"is_claimable":false,"name":"Discovery of Novel Digital Biomarkers for Type 2 Diabetic Nephropathy Classification via Integration of Urinary Proteomics and Pathology.","description":"<h4>Background</h4>The heterogeneous phenotype of diabetic nephropathy (DN) from type 2 diabetes complicates appropriate treatment approaches and outcome prediction. Kidney histology helps diagnose DN and predict its outcomes, and an artificial intelligence (AI)-based approach will maximize clinical utility of histopathological evaluation. Herein, we addressed whether AI-based integration of urine proteomics and image features improves DN classification and its outcome prediction, altogether augmenting and advancing pathology practice.<h4>Methods</h4>We studied whole slide images (WSIs) of periodic acid-Schiff-stained kidney biopsies from 56 DN patients with associated urinary proteomics data. We identified urinary proteins differentially expressed in patients who developed end-stage kidne","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 May","modification":"2026-05-14T03:17:27.631Z","creation":"2026-05-14T03:08:39.255Z"},"accession":"S-EPMC10187347","cross_references":{"pubmed":["37205413"],"doi":["10.1101/2023.04.28.23289272"]}}