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Applications of AI (391) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (232) Decision Support for Health Professionals (1705) Electronic Health Records (1425) Pharmacology and Pharmaceutics (134) Machine Learning (2317) Registered Report (884) Antimicrobial Stewardship and Antibiotic Resistance (73)

Published on in Vol 5 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/81103, first published .
Scientist in blue gloves holds orange and white pills, with blood samples and microscope in background.

Improving Vancomycin Therapeutic Drug Monitoring With a Deep Learning–Based Two-Compartment Predictive Model: Development and Validation Study

Improving Vancomycin Therapeutic Drug Monitoring With a Deep Learning–Based Two-Compartment Predictive Model: Development and Validation Study

Authors of this article:

Bingyu Mao1 Author Orcid Image ;   Ziqian Xie1 Author Orcid Image ;   Laila Rasmy1 Author Orcid Image ;   Masayuki Nigo2 Author Orcid Image ;   Degui Zhi1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Bingyu Mao   1 * , PhD ;   Ziqian Xie   1 * , PhD ;   Laila Rasmy   1 , PhD ;   Masayuki Nigo   2 , MD ;   Degui Zhi   1 , PhD

1 McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States

2 Division of Infectious Diseases, Houston Methodist, Houston, TX, United States

*these authors contributed equally

Corresponding Author:

  • Degui Zhi, PhD
  • McWilliams School of Biomedical Informatics
  • The University of Texas Health Science Center at Houston
  • 7000 Fannin, Suite 600
  • Houston, TX
  • United States
  • Phone: 1 713-500-3629
  • Fax: 1 713-500-3929
  • Email: Degui.Zhi@uth.tmc.edu