Implementation of machine learning study in Staphylococcus aureus’s FTIR spectra to antibiotic resistance identification

Antibiotic is one of the most important medical inventions in the 20th century ¹. However, bacterial resistance to antibiotics is becoming a global health-care problem ². One of the important measures to tackle this problem is fast detection bacterial antibiotic susceptibility ¹. In this research topic and inspired by the work report of Soares et. al. ³,⁴ we were motivated to developed this study to identification of resistance to antibiotic in Staphylococcus aureus. By mean of machine learning implementation in data analyses of Fourier-Transform Infrared Spectroscopy (FTIR) spectra, we found promisor results in samples with and without antibiotic resistance develop.