Artificial intelligence-clinical decision support system for enhanced infectious disease management: Accelerating ceftazidime-avibactam resistance detection in Klebsiella pneumoniae.
Journal:
Journal of infection and public health
PMID:
39270470
Abstract
BACKGROUND: Effective and rapid diagnostic strategies are required to manage antibiotic resistance in Klebsiella pneumonia (KP). This study aimed to design an artificial intelligence-clinical decision support system (AI-CDSS) using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and machine learning for the rapid detection of ceftazidime-avibactam (CZA) resistance in KP to improve clinical decision-making processes.
Authors
Keywords
Anti-Bacterial Agents
Artificial Intelligence
Azabicyclo Compounds
Ceftazidime
Decision Support Systems, Clinical
Drug Combinations
Drug Resistance, Multiple, Bacterial
Humans
Klebsiella Infections
Klebsiella pneumoniae
Machine Learning
Microbial Sensitivity Tests
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization