Innovative strategies against superbugs: Developing an AI-CDSS for precise Stenotrophomonas maltophilia treatment.

Tai-Han LinHsing-Yi ChungMing-Jr JianChih-Kai ChangHung-Hsin LinChing-Mei YuCherng-Lih PerngFeng-Yee ChangChien-Wen ChenHung-Sheng Shang

Published in: Journal of global antimicrobial resistance (2024)

MALDI-TOF MS and machine learning integration into an AI-CDSS significantly improved rapid SM resistance detection. This system reduced the identification time of resistant strains from 24 h to minutes after MALDI-TOF MS identification, providing timely and data-driven guidance. Combining MALDI-TOF MS with machine learning could enhance clinical decision-making and improve SM infection treatment outcomes.

Keyphrases

machine learning
artificial intelligence
mass spectrometry
decision making
loop mediated isothermal amplification
big data
bioinformatics analysis
escherichia coli
deep learning
real time pcr