Research Information System
3rd International Artificial Intelligence Health Congress, İzmir, Turkey, 11 - 13 May 2022, pp.33
Artificial intelligence which became important in the
laboratory is used in clinical microbiology in infectious
disease testing to support decision-making, in image
analysis, digital plate reading, matrix-assisted laser
desorption-ionization/time of flight mass spectrometry,
and Raman- based identification and antimicrobial
susceptibility testing. Antimicrobial resistance is a
worldwide risk for human health. Treatment of infections
requires fast and correct identification and antimicrobial
susceptibility testing. Current microbiology laboratory
procedures give broad information in identification
and antimicrobial susceptibility testing, however, they
are complex and time-consuming. Thus, new methods
are required such as Raman technologies. Vibrational
spectroscopy method Raman spectroscopy is one of the
useful and new tools that is used in different fields of
medicine. Recently, fast and accurate Raman technologies
used identification, differentiation of resistant and
sensitive strains, and antimicrobial susceptibility testing
became important in microbiology. Raman technologies
include the methods Raman scattering, surfaceenhanced Raman scattering, coherent Raman scattering
imaging. Raman spectroscopy has the characteristics
of applying bacterial detection, identification, and,
antibiotic susceptibility testing all at once with high
accuracy. It is a cheap, label-free, and effective method
that differentiate bacterial infections. Besides bacteria, it
is also used in rapid and sensitive virus detection such as
COVID-19 by using saliva. When PCR is used in COVID-19
detection, as the variants increase sensitivity decreases.
Raman technology overcomes this problem. This review
summarizes the applications, challenges, and future of
Raman technologies in microbiology to improve the
treatment of infectious diseases and to improve human
health