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| Machine Learning to Compare Frequent Medical Problems of African American and Caucasian Diabetic Kidney Patients |
| Yong-Mi Kim, Pranay Kathuria, Dursun Delen |
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Healthc Inform Res. 2017;23(4):241-248. Published online October 31, 2017 DOI: https://doi.org/10.4258/hir.2017.23.4.241 |
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Machine Learning to Compare Frequent Medical Problems of African American and Caucasian Diabetic Kidney Patients Healthcare Informatics Research. 2017;23(4):241  Creating a Machine Learning Tool to Predict Acute Kidney Injury in African American Hospitalized Patients Pharmacy. 2022;10(4):68 Do frequent fingersticks improve glycemic control in nursing home diabetic patients? Journal of the American Medical Directors Association. 2007;8(3):B7 Immune Gene Signature Expression Differs between African American and Caucasian Patients with Renal Cell Carcinoma Kidney Cancer. 2022;1-6 Kidney Age Index (KAI): A novel age-related biomarker to estimate kidney function in patients with diabetic kidney disease using machine learning Computer Methods and Programs in Biomedicine. 2021;211:106434 POS-325 Prediction of 3-Year Risk of Diabetic Kidney Disease Using Machine Learning Based on Electronic Medical Records Kidney International Reports. 2022;7(2):S146-S147 Predicting diagnostic gene biomarkers in patients with diabetic kidney disease based on weighted gene co-expression network analysis and machine-learning algorithms . 2022; Transplant Rates in Frequent Hemodialysis and Matched Thrice-Weekly Hemodialysis Patients American Journal of Kidney Diseases. 2012;59(4):B89 79: Idiopathic Nodular Glomerulosclerosis in a Non-Diabetic Young Caucasian Male With Metabolic Syndrome: A Case Report American Journal of Kidney Diseases. 2010;55(4):B51 Hemodialysis in diabetic patients American Journal of Kidney Diseases. 2001;38(4):S195-S199 |
