Is it possible to determine antibiotic resistance of E. coli by analyzing laboratory data with machine learning?

Abstract

Microbial antibiotic resistance remains a serious public health problem worldwide. Conventional culture-based techniques are time-taking procedures; therefore, there is need for new approaches for detecting bacterial resistance. The aim of this study was to assess antibiotic resistance of Escherichia coli by analyzing biochemical parameters with machine learning systems without using antibiogram.

Keywords

• antibiotic resistance
• diagnostic decision making
• laboratory medicine
• machine learning
• urinary tract infection
• i̇drar yolu enfeksiyonu
• makine öğrenimi
• laboratuvar tıbbı
• tanısal karar verme
• antibiyotik direnci