Confidence-based prediction of antibiotic resistance at the patient level.

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Bibliographic Details
Title: Confidence-based prediction of antibiotic resistance at the patient level.
Authors: Inda-Díaz JS; Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.; Center for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden.; Centre for Microbiome Research, School of Biomedical Sciences, Queensland University of Technology, Translational Research Institute, Woolloongabba, Australia., Johnning A; Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.; Center for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden.; Department of Systems and Data Analysis, Fraunhofer-Chalmers Center, Gothenburg, Sweden., Hessel M; Center for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden.; Department of Clinical Microbiology, Sahlgrenska University Hospital, Gothenburg, Sweden., Sjöberg A; Department of Systems and Data Analysis, Fraunhofer-Chalmers Center, Gothenburg, Sweden.; Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden., Lokrantz A; Department of Systems and Data Analysis, Fraunhofer-Chalmers Center, Gothenburg, Sweden., Helldal L; Department of Clinical Microbiology, Sahlgrenska University Hospital, Gothenburg, Sweden., Jirstrand M; Department of Systems and Data Analysis, Fraunhofer-Chalmers Center, Gothenburg, Sweden.; Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden., Svensson L; Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden., Kristiansson E; Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.; Center for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden.
Source: MBio [mBio] 2026 Feb 11; Vol. 17 (2), pp. e0343125. Date of Electronic Publication: 2026 Jan 23.
Publication Type: Journal Article
Journal Info: Publisher: American Society for Microbiology Country of Publication: United States NLM ID: 101519231 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2150-7511 (Electronic) NLM ISO Abbreviation: mBio Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2150-7511
DOI:10.1128/mbio.03431-25