通过机器学习算法比较完整病毒和灭活病毒的 SERS 光谱,用于病毒性疾病的诊断应用

IF 2.5 3区 物理与天体物理 Q3 MATERIALS SCIENCE, MULTIDISCIPLINARY Photonics and Nanostructures-Fundamentals and Applications Pub Date : 2024-06-20 DOI:10.1016/j.photonics.2024.101290
Olga Andreeva , Artem Tabarov , Konstantin Grigorenko , Alexander Dobroslavin , Azat Gazizulin , Andrey Gorshkov , Alyona Zheltukhina , Nina Gavrilova , Daria Danilenko , Vladimir Vitkin
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引用次数: 0

摘要

在这项工作中,使用了表面增强拉曼光谱(SERS)和机器学习算法(MLA)来检测病毒颗粒并对其进行分类,以评估使用灭活甲型流感病毒的光谱进行MLA训练和光谱数据库编制的可能性,从而进一步研究和诊断完整形式的病毒。病毒颗粒灭活是通过福尔马林、紫外线和β-丙内酯进行的。通过支持向量法和主成分分析,对完整和失活病毒颗粒光谱进行了分类,准确率为 80.0-96.7%。研究结果表明,根据灭活病毒颗粒的光谱建立光谱数据库并训练机器学习算法以进一步应用于完整病毒的 SERS 诊断并不可取。
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Comparison of SERS spectra of intact and inactivated viruses via machine learning algorithms for the viral disease’s diagnosis application

In this work, Surface-enhanced Raman spectroscopy (SERS) along with machine learning algorithms (MLA) were used to detect and classify the viral particles to assess the possibility of using the spectra of inactivated influenza A viruses for MLA training and spectra database compilation for further study and diagnosis of intact forms of the virus. Viral particles inactivation was performed by formalin, ultraviolet and beta-propiolactone. Support vector method and principal component analysis allowed to classify intact and inactivated viral particles spectra with an accuracy of 80.0–96.7 %. The results obtained suggest that it is not advisable to create a spectral database and train machine learning algorithms for their further application in SERS diagnostics of intact viruses based on the spectra of the inactivated virus particles.

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来源期刊
CiteScore
5.00
自引率
3.70%
发文量
77
审稿时长
62 days
期刊介绍: This journal establishes a dedicated channel for physicists, material scientists, chemists, engineers and computer scientists who are interested in photonics and nanostructures, and especially in research related to photonic crystals, photonic band gaps and metamaterials. The Journal sheds light on the latest developments in this growing field of science that will see the emergence of faster telecommunications and ultimately computers that use light instead of electrons to connect components.
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