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Automated web-based typing of Clostridioides difficile ribotypes via MALDI-TOF MS

Abstract Background Clostridioides difficile is a major cause of hospital-acquired diarrhea and a driver of nosocomial outbreaks, yet rapid, accurate ribotype identification remains challenging. We sought to develop a MALDI-TOF MS–based workflow coupled with machine learning to distinguish epidemic...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Mario Blázquez-Sánchez, Alejandro Guerrero-López, Ana Candela, Albert Belenguer-Llorens, José Miguel Moreno, Carlos Sevilla-Salcedo, María Sánchez-Cueto, Manuel J. Arroyo, Mark Gutiérrez-Pareja, Vanessa Gómez-Verdejo, Pablo M. Olmos, Luis Mancera, Patricia Muñoz, Mercedes Marín, Luis Alcalá, David Rodríguez-Temporal, Belén Rodríguez-Sánchez
Format: Artigo
Sprache:Inglês
Veröffentlicht: BMC 2025-07-01
Schriftenreihe:BMC Bioinformatics
Schlagworte:
Clostridioides difficile
Clostridium difficile
MALDI-TOF MS
Machine learning
Ribotyping
Outbreak
Online-Zugang:https://doi.org/10.1186/s12859-025-06200-6
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