This paper is in the following e-collection/theme issue:

Clinical Information and Decision Making (1915) Tools, Programs and Algorithms (376) Machine Learning (2076) New Methods (1134) Antimicrobial Stewardship and Antibiotic Resistance (62) Pharmacovigilance (171)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/63983, first published .
Optimizing Initial Vancomycin Dosing in Hospitalized Patients Using Machine Learning Approach for Enhanced Therapeutic Outcomes: Algorithm Development and Validation Study

Optimizing Initial Vancomycin Dosing in Hospitalized Patients Using Machine Learning Approach for Enhanced Therapeutic Outcomes: Algorithm Development and Validation Study

Optimizing Initial Vancomycin Dosing in Hospitalized Patients Using Machine Learning Approach for Enhanced Therapeutic Outcomes: Algorithm Development and Validation Study

Authors of this article:

Heonyi Lee1 Author Orcid Image ;   Yi-Jun Kim2, 3 Author Orcid Image ;   Jin-Hong Kim4 Author Orcid Image ;   Soo-Kyung Kim5 Author Orcid Image ;   Tae-Dong Jeong5 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Yang Y, Yan H, Wang X, Lao J, Zhang R, Chen Z, Ma S, Li Y, Li X. Clinical risk assessment of serum creatinine abnormalities during vancomycin therapy: a retrospective study using machine learning models. International Journal of Clinical Pharmacy 2025;47(6):1830 View