Label-free laser spectroscopy for respiratory virus detection: A review

Авторы: Kistenev Yury V., Das Anubhab, Mazumder Nirmal, Cherkasova Olga P., Knyazkova Anastasia I., Shkurinov Alexander P., Tuchin Valery V., Lednev Igor K.
Журнал: Journal of Biophotonics
Номер: n/a
Год издания: 2022
Издательство: Wiley - VCH Verlag GmbH & CO. KGaA
Местоположение издательства: Germany
Первая страница: e202200100
DOI: 10.1002/jbio.202200100
Аннотация: Abstract Infectious diseases are among the most severe threats to modern society. Current methods of virus infection detection based on genome tests need reagents and specialized laboratories. The desired characteristics of new virus detection methods are noninvasiveness, simplicity of implementation, real-time, low cost and label-free detection. There are two groups of methods for molecular biomarkers’ detection and analysis: (i) a sample physical separation into individual molecular components and their identification, and (ii) sample content analysis by laser spectroscopy. Variations in the spectral data are typically minor. It requires the use of sophisticated analytical methods like machine learning. This review examines the current technological level of laser spectroscopy and machine learning methods in applications for virus infection detection.
Добавил в систему: Шкуринов Александр Павлович

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