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

Formative Evaluation of Digital Health Interventions (2491) Artificial Intelligence (1421) Machine Learning (1501) Pharmacology and Pharmaceutics (70) Intensive Care Unit (ICU) (114) Clinical Information and Decision Making (1434) Decision Support for Health Professionals (1210)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45202, first published .
A Deep Learning–Based Approach for Prediction of Vancomycin Treatment Monitoring: Retrospective Study Among Patients With Critical Illness

A Deep Learning–Based Approach for Prediction of Vancomycin Treatment Monitoring: Retrospective Study Among Patients With Critical Illness

A Deep Learning–Based Approach for Prediction of Vancomycin Treatment Monitoring: Retrospective Study Among Patients With Critical Illness

Authors of this article:

Dohyun Kim1 Author Orcid Image ;   Hyun-Soo Choi1, 2 Author Orcid Image ;   DongHoon Lee1 Author Orcid Image ;   Minkyu Kim1 Author Orcid Image ;   Yoon Kim1, 3 Author Orcid Image ;   Seon-Sook Han4 Author Orcid Image ;   Yeonjeong Heo4 Author Orcid Image ;   Ju-Hee Park5 Author Orcid Image ;   Jinkyeong Park6 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Journals

  1. Núñez R, Doña I, Cornejo-García J. Predictive models and applicability of artificial intelligence-based approaches in drug allergy. Current Opinion in Allergy & Clinical Immunology 2024;24(4):189 View
  2. Gonçalves Pereira J, Fernandes J, Mendes T, Gonzalez F, Fernandes S. Artificial Intelligence to Close the Gap between Pharmacokinetic/Pharmacodynamic Targets and Clinical Outcomes in Critically Ill Patients: A Narrative Review on Beta Lactams. Antibiotics 2024;13(9):853 View