Machine learning models to predict the warfarin discharge dosage using clinical information of inpatients from South Korea.

ABSTRACT: As warfarin has a narrow therapeutic window and obvious response variability among individuals, it is difficult to rapidly determine personalized warfarin dosage. Adverse drug events(ADE) resulting from warfarin overdose can be critical, so that typically physicians adjust the warfarin dosage through the INR monitoring twice a week when starting warfarin. Our study aimed to develop machine learning (ML) models that predicts the discharge dosage of warfarin as the initial warfarin dosage using clinical data derived from electronic medical records within 2 days of hospitalization. During this retrospective study, adult patients who were prescribed warfarin at Asan Medical Center (AMC) between January 1, 2018, and October 31, 2020, were recruited as a model development cohort (n = 3168). Addi

SUBMITTER: Choi H 

PROVIDER: S-EPMC10725866 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature