Data limitations hinder the development of AI-based decision support for the treatment of antibiotic-resistant bacteria
Other text in scientific journal, 2025
No abstract available
data limitations
antimicrobial resistance
decision support
machine learning
AI
bacterial infections
Author
Anna Johnning
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
University of Gothenburg
Fraunhofer-Chalmers Centre
Styrbjörn Käll
Semcon
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
University of Gothenburg
Erik Kristiansson
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
University of Gothenburg
Future Microbiology
1746-0913 (ISSN) 1746-0921 (eISSN)
Vol. 20 15 993-995Nya elektrokemiska biosensorer och artificiell intelligens för förbättrad diagnostik avledprotesinfektioner orsakade av antibiotikaresistenta bakterier
Swedish Research Council (VR) (2023-01685), 2024-01-01 -- 2026-12-31.
Clinical evaluation of AI-driven decision support for the treatment of infections caused by antibiotic-resistant bacteria
Swedish Research Council (VR) (2024-06177), 2024-12-01 -- 2026-11-30.
Nya elektrokemiska biosensorer och artificiell intelligens för förbättrad diagnostik avledprotesinfektioner orsakade av antibiotikaresistenta bakterier
Swedish Research Council (VR) (2023-01685), 2024-01-01 -- 2026-12-31.
Datadriven Life Science 2024-2026, fas 2
Knut and Alice Wallenberg Foundation (2024.0159), 2024-04-01 -- 2026-03-31.
Subject Categories (SSIF 2025)
Clinical Medicine
Basic Medicine
Health Sciences
DOI
10.1080/17460913.2025.2572907
PubMed
41071030