Machine Learning Tools for Predicting Pediatric Urinary Tract Infections Caused by ESBL-producing Bacteria
Our study indicates that machine learning models based on data available at UTI presentation may support clinicians in estimating the likelihood of ESBL-producing bacteria UTIs. Prospective studies are required to improve the models' performance and determine their actual impact on clinical outcomes.
Authors
- Vered Shkalim Zemer (ORCID: https://orcid.org/0000-0003-1733-5395)
- Shiri Kushnir (ORCID: https://orcid.org/0000-0003-2359-5249)
- Chen Hajaj (ORCID: https://orcid.org/0000-0001-9940-5654)
- Shani Alkoby (ORCID: https://orcid.org/0000-0002-0582-5832)
- Yael Reichenberg
- Avner Herman Cohen
- Shai Ashkenazi
Institutions
- Tel Aviv University (IL)
- Rabin Medical Center (IL)
- Schneider Children's Medical Center (IL)
- Ariel University (IL)
- Clalit Health Services (IL)
Publication Details
- Journal
- The Pediatric Infectious Disease Journal
- Published
- 2026-02-12
- DOI
- https://doi.org/10.1097/inf.0000000000005179
- Primary Topic
- Urinary Tract Infections Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00