Identification of methicillin-resistant Staphylococcus aureus bacteria using surface-enhanced Raman spectroscopy and machine learning techniques-Reference-Cited by-同舟云学术

Identification of methicillin-resistant Staphylococcus aureus bacteria using surface-enhanced Raman spectroscopy and machine learning techniques

Published:2020 Issue:23 Volume:145 Page:7559-7570
ISSN:0003-2654
Container-title:The Analyst
language:en
Short-container-title:Analyst

Author:

Uysal Ciloglu Fatma¹²³⁴,Saridag Ayse Mine⁵⁶⁷⁴,Kilic Ibrahim Halil⁸⁶⁷⁴,Tokmakci Mahmut¹²³⁴,Kahraman Mehmet⁵⁶⁷⁴,Aydin Omer¹²³⁴⁹^ORCID

Affiliation:

1. Department of Biomedical Engineering

2. Erciyes University

3. Kayseri 38039

4. Turkey

5. Department of Chemistry

6. Gaziantep University

7. Gaziantep 27310

8. Department of Biology

9. ERNAM-Nanotechnology Research and Application Center

Abstract

Herein, surface-enhanced Raman spectroscopy (SERS) combined with supervised and unsupervised machine learning techniques were used for the identification of methicillin-resistant and methicillin-sensitive Staphylococcus aureus.

Funder

Türkiye Bilimler Akademisi

Türkiye Bilimsel ve Teknolojik Araştirma Kurumu

Erciyes Üniversitesi

Publisher

Royal Society of Chemistry (RSC)

Subject

Electrochemistry,Spectroscopy,Environmental Chemistry,Biochemistry,Analytical Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2020/AN/D0AN00476F

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4. Antibiotic resistance management

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