A machine learning driven monogram for predicting chronic kidney disease stages 3-5.

ABSTRACT: Chronic kidney disease (CKD) remains one of the most prominent global causes of mortality worldwide, necessitating accurate prediction models for early detection and prevention. In recent years, machine learning (ML) techniques have exhibited promising outcomes across various medical applications. This study introduces a novel ML-driven monogram approach for early identification of individuals at risk for developing CKD stages 3-5. This retrospective study employed a comprehensive dataset comprised of clinical and laboratory variables from a large cohort of diagnosed CKD patients. Advanced ML algorithms, including feature selection and regression models, were applied to build a predictive model. Among 467 participants, 11.56% developed CKD stages 3-5 over a 9-year follow-up. Several factor

SUBMITTER: Ghosh SK 

PROVIDER: S-EPMC10703939 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature