A hybrid learning approach to better classify exhaled breath's infrared spectra: A noninvasive optical diagnosis for socially significant diseases

IF 2 3区 物理与天体物理 Q3 BIOCHEMICAL RESEARCH METHODS Journal of Biophotonics Pub Date : 2024-07-29 DOI:10.1002/jbio.202400151
Igor Semenovich Golyak, Dmitriy Romanovich Anfimov, Pavel Pavlovich Demkin, Pavel Vyacheslavovich Berezhanskiy, Olga Aleksandrovna Nebritova, Andrey Nikolaevich Morozov, Igor Leonidovich Fufurin
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Abstract

Early diagnosis is crucial for effective treatment of socially significant diseases, such as type 1 diabetes mellitus (T1DM), pneumonia, and asthma. This study employs a diagnostic method based on infrared laser spectroscopy of human exhaled breath. The experimental setup comprises a quantum cascade laser, which emits in a pulsed mode with a peak power of up to 150 mW in the spectral range of 5.3–12.8 μm (780–1890 cm−1), and a Herriott multipass gas cell with a specific optical path length of 76 m. Using this setup, spectra of exhaled breath in the mid-infrared range were obtained from 165 volunteers, including healthy individuals, patients with T1DM, asthma, and pneumonia. The study proposes a hybrid approach for classifying these spectra, utilizing a variational autoencoder for dimensionality reduction and a support vector machine method for classification. The results demonstrate that the proposed hybrid approach outperforms other machine learning method combinations.

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混合学习法更好地对呼出气体的红外光谱进行分类:针对社会重大疾病的无创光学诊断。
早期诊断对于有效治疗 1 型糖尿病(T1DM)、肺炎和哮喘等具有重大社会影响的疾病至关重要。本研究采用了一种基于人体呼出气体红外激光光谱的诊断方法。实验装置由一个量子级联激光器和一个特定光路长度为 76 米的赫里奥特多通道气体池组成,量子级联激光器以脉冲模式发射,在 5.3-12.8 μm(780-1890 cm-1)光谱范围内的峰值功率可达 150 mW。利用这一装置,获得了 165 名志愿者呼出气体在中红外范围内的光谱,其中包括健康人、T1DM 患者、哮喘患者和肺炎患者。研究提出了一种对这些光谱进行分类的混合方法,利用变异自动编码器进行降维,并利用支持向量机方法进行分类。结果表明,所提出的混合方法优于其他机器学习方法组合。
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来源期刊
Journal of Biophotonics
Journal of Biophotonics 生物-生化研究方法
CiteScore
5.70
自引率
7.10%
发文量
248
审稿时长
1 months
期刊介绍: The first international journal dedicated to publishing reviews and original articles from this exciting field, the Journal of Biophotonics covers the broad range of research on interactions between light and biological material. The journal offers a platform where the physicist communicates with the biologist and where the clinical practitioner learns about the latest tools for the diagnosis of diseases. As such, the journal is highly interdisciplinary, publishing cutting edge research in the fields of life sciences, medicine, physics, chemistry, and engineering. The coverage extends from fundamental research to specific developments, while also including the latest applications.
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