{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T15:41:58Z","timestamp":1773416518029,"version":"3.50.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686080","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,7]]},"abstract":"<jats:p>Chronic Kidney Disease (CKD) is a prevalent and progressive condition that can lead to end-stage renal disease (ESRD) if left unmanaged. Accurate prediction of CKD progression, particularly in patients with CKD stages 3\u20135, is essential for early intervention and personalized treatment. This study utilized machine learning (ML) models to predict declines in estimated glomerular filtration rate (eGFR) over one year. The models, including LGBM and Random Forest, were trained on a large cohort of CKD patients from the Taipei Medical University Clinical Research Database (TMUCRD). LightGBM emerged as the top-performing model with AUC values of 0.76 and 0.82 for predicting 5% and 25% declines in eGFR, respectively. SHAP (Shapley Additive Explanations) analysis identified baseline eGFR, eGFR slope, and BUN as key predictive features. The results demonstrate the utility of ML in CKD management and highlight the importance of personalized prediction models for improving patient outcomes.<\/jats:p>","DOI":"10.3233\/shti251022","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:38:26Z","timestamp":1754566706000},"source":"Crossref","is-referenced-by-count":2,"title":["Personalized Prediction of Chronic Kidney Disease Progression in Patients with Chronic Kidney Disease Stages 3\u20135: A Multicenter Study Using the Machine Learning Approach"],"prefix":"10.3233","author":[{"given":"Trung","family":"Toan Duong","sequence":"first","affiliation":[{"name":"International PhD program of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan"},{"name":"Cho Ray Hospital, Ministry of Health, Ho Chi Minh City, Vietnam"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minh Tri","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Institute of Data Science, College of Management, Taipei Medical University, New Taipei City, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chia Te","family":"Liao","sequence":"additional","affiliation":[{"name":"Division of Nephrology, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan"},{"name":"Division of Nephrology, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan"},{"name":"TMU Research Center of Urology and Kidney, Taipei Medical University, Taipei, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ngoc Hoang","family":"Le","sequence":"additional","affiliation":[{"name":"Graduate of Biomedical Materials and Tissue Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thanh Phuc","family":"Phan","sequence":"additional","affiliation":[{"name":"International PhD program of Biotech and Healthcare Management, College of Management, Taipei Medical University, Taipei, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chih Wei","family":"Huang","sequence":"additional","affiliation":[{"name":"Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan"},{"name":"International Center for Health Information Technology, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jason C.","family":"Hsu","sequence":"additional","affiliation":[{"name":"International PhD program of Biotech and Healthcare Management, College of Management, Taipei Medical University, Taipei, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alex P.A.","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Graduate Institute of Data Science, College of management, Taipei Medical University, Taipei, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2025 \u2014 Healthcare Smart \u00d7 Medicine Deep"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI251022","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:38:37Z","timestamp":1754566717000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI251022"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti251022","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,7]]}}}