Machine Learning Prediction Models for Chronic Kidney Disease Using National Health Insurance Claim Data in Taiwan.

ABSTRACT: Chronic kidney disease (CKD) represents a heavy burden on the healthcare system because of the increasing number of patients, high risk of progression to end-stage renal disease, and poor prognosis of morbidity and mortality. The aim of this study is to develop a machine-learning model that uses the comorbidity and medication data obtained from Taiwan's National Health Insurance Research Database to forecast the occurrence of CKD within the next 6 or 12 months before its onset, and hence its prevalence in the population. A total of 18,000 people with CKD and 72,000 people without CKD diagnosis were selected using propensity score matching. Their demographic, medication and comorbidity data from their respective two-year observation period were used to build a predictive model. Among the ap

SUBMITTER: Krishnamurthy S 

PROVIDER: S-EPMC8151834 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature