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

Formative Evaluation of Digital Health Interventions (2206) Data Science (225) Machine Learning (1382) Nosocomial Infections (16) Perioperative Infection Control and Prevention (6) Natural Language Processing (643) Antimicrobial Stewardship and Antibiotic Resistance (37)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54044, first published .
Predictive Model for Extended-Spectrum β-Lactamase–Producing Bacterial Infections Using Natural Language Processing Technique and Open Data in Intensive Care Unit Environment: Retrospective Observational Study

Predictive Model for Extended-Spectrum β-Lactamase–Producing Bacterial Infections Using Natural Language Processing Technique and Open Data in Intensive Care Unit Environment: Retrospective Observational Study

Predictive Model for Extended-Spectrum β-Lactamase–Producing Bacterial Infections Using Natural Language Processing Technique and Open Data in Intensive Care Unit Environment: Retrospective Observational Study

Authors of this article:

Genta Ito1 Author Orcid Image ;   Shuntaro Yada1 Author Orcid Image ;   Shoko Wakamiya1 Author Orcid Image ;   Eiji Aramaki1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Genta Ito   1 , BPharm ;   Shuntaro Yada   1 , PhD ;   Shoko Wakamiya   1 , PhD ;   Eiji Aramaki   1 , Prof Dr

1 Department of Information Science, Nara Institute of Science and Technology, Ikoma City, Japan

Corresponding Author:

  • Eiji Aramaki, Prof Dr
  • Department of Information Science
  • Nara Institute of Science and Technology
  • 8916-5 Takayama-cho
  • Ikoma City, 8916-5
  • Japan
  • Phone: 81 0743725204
  • Email: aramaki@is.naist.jp