{"ID":2870200,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.12704","arxiv_id":"2509.12704","title":"NORA: A Nephrology-Oriented Representation Learning Approach Towards Chronic Kidney Disease Classification","abstract":"Chronic Kidney Disease (CKD) affects millions of people worldwide, yet its early detection remains challenging, especially in outpatient settings where laboratory-based renal biomarkers are often unavailable. In this work, we investigate the predictive potential of routinely collected non-renal clinical variables for CKD classification, including sociodemographic factors, comorbid conditions, and urinalysis findings. We introduce the Nephrology-Oriented Representation leArning (NORA) approach, which combines supervised contrastive learning with a nonlinear Random Forest classifier. NORA first derives discriminative patient representations from tabular EHR data, which are then used for downstream CKD classification. We evaluated NORA on a clinic-based EHR dataset from Riverside Nephrology Physicians. Our results demonstrated that NORA improves class separability and overall classification performance, particularly enhancing the F1-score for early-stage CKD. Additionally, we assessed the generalizability of NORA on the UCI CKD dataset, demonstrating its effectiveness for CKD risk stratification across distinct patient cohorts.","short_abstract":"Chronic Kidney Disease (CKD) affects millions of people worldwide, yet its early detection remains challenging, especially in outpatient settings where laboratory-based renal biomarkers are often unavailable. In this work, we investigate the predictive potential of routinely collected non-renal clinical variables for C...","url_abs":"https://arxiv.org/abs/2509.12704","url_pdf":"https://arxiv.org/pdf/2509.12704v1","authors":"[\"Mohammad Abdul Hafeez Khan\",\"Twisha Bhattacharyya\",\"Omar Khan\",\"Noorah Khan\",\"Alina Aziz Fatima Khan\",\"Mohammed Qutub Khan\",\"Sujoy Ghosh Hajra\"]","published":"2025-09-16T05:54:33Z","proceeding":"cs.LG","tasks":"[\"cs.LG\"]","methods":"[]","has_code":false}