Data-Driven Two-Stage Framework for Identification and Characterization of Different Antibiotic-Resistant Escherichia coli Isolates Based on Mass Spectrometry Data

Author:

Chung Chia-Ru1ORCID,Wang Hsin-Yao23ORCID,Yao Chun-Han1,Wu Li-Ching4,Lu Jang-Jih256ORCID,Horng Jorng-Tzong17,Lee Tzong-Yi8ORCID

Affiliation:

1. Department of Computer Science and Information Engineering, National Central University, Taoyuan, Taiwan

2. Department of Laboratory Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan

3. Ph.D. Program in Biomedical Engineering, Chang Gung University, Taoyuan, Taiwan

4. Department of Biomedical Sciences and Engineering, National Central University, Taoyuan, Taiwan

5. College of Medicine, Chang Gung University, Taoyuan, Taiwan

6. Department of Medical Biotechnology and Laboratory Science, Chang Gung University, Taoyuan, Taiwan

7. Department of Bioinformatics and Medical Engineering, Asia University, Taichung, Taiwan

8. Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan

Abstract

Based on a large amount of matrix-assisted laser desorption ionization–time-of-flight mass spectrometry (MALDI-TOF MS) clinical data, comprising 37,918 Escherichia coli isolates, a data-driven two-stage framework was established to evaluate the antimicrobial resistance of E. coli . Five antibiotics, including amoxicillin (AMC), ceftazidime (CAZ), ciprofloxacin (CIP), ceftriaxone (CRO), and cefuroxime (CXM), were considered for the two-stage model training, and the values of the area under the receiver operating characteristic curve (AUC) were 0.62 for AMC, 0.72 for CAZ, 0.87 for CIP, 0.72 for CRO, and 0.72 for CXM.

Publisher

American Society for Microbiology

Subject

Infectious Diseases,Cell Biology,Microbiology (medical),Genetics,General Immunology and Microbiology,Ecology,Physiology

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