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Diagnosis of Diabetes Based on Analysis of Exhaled Air by Terahertz Spectroscopy and Machine Learning

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Abstract

Results of studying the exhaled air of patients with diabetes mellitus in comparison with healthy volunteers with the use of broadband terahertz time-domain spectroscopy are presented. Typical spectral subranges in which absorption spectrum profiles of breath tests of the target and control group differ most significantly are revealed: 0.560, 0.738, 0.970, 1.070, 1.140, 1.180, and 1.400 THz. Using the principal component analysis, it is shown that the set of absorption coefficients in these regions allows one to reliably separate the target and control groups. The obtained results are compared with measurements of acetone vapors in the exhaled air of patients with diabetes mellitus and healthy volunteers.

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Funding

This work was performed within the framework of the Basic Research Program for State Academies of Sciences for 2013–2020, direction III.23. The study was supported by  the Russian Foundation for Basic Research, project nos. 18-52-16025 and 17-00-00275 (17-00-00272, 17-00-00184, and 17-00-00186).

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Authors and Affiliations

  1. National Research Tomsk State University, 634050, Tomsk, Russia

    Yu. V. Kistenev, A. I. Knyazkova, O. A. Zakharova, E. S. Sim, I. Yu. Yanina, V. V. Tuchin & A. V. Borisov

  2. Siberian State Medical University, 634050, Tomsk, Russia

    Yu. V. Kistenev, A. V. Teteneva, T. V. Sorokina, E. S. Sim & A. V. Borisov

  3. Institute of Strength Physics and Materials Science, Siberian Branch, Russian Academy of Sciences, 634055, Tomsk, Russia

    A. I. Knyazkova & O. A. Zakharova

  4. Université du Littoral-Côte d’Opale, 59140, Dunkerque, France

    A. Cuisset

  5. Institute for Physics of Microstructures, Russian Academy of Sciences, 603087, Nizhny Novgorod, Russia

    V. L. Vaks, E. G. Domracheva, M. B. Chernyaeva & V. A. Anfert’ev

  6. Saratov National Research State University, 410012, Saratov, Russia

    I. Yu. Yanina & V. V. Tuchin

  7. St. Petersburg National Research University of Information Technologies, Mechanics, and Optics (ITMO University), 197101, St. Petersburg, Russia

    V. V. Tuchin

Authors
  1. Yu. V. Kistenev
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  2. A. V. Teteneva
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  3. T. V. Sorokina
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  4. A. I. Knyazkova
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  5. O. A. Zakharova
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  6. A. Cuisset
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  7. V. L. Vaks
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  8. E. G. Domracheva
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  9. M. B. Chernyaeva
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  10. V. A. Anfert’ev
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  11. E. S. Sim
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  12. I. Yu. Yanina
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  13. V. V. Tuchin
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  14. A. V. Borisov
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Corresponding author

Correspondence to Yu. V. Kistenev.

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COMPLIANCE WITH ETHICAL STANDARDS

All procedures performed in this study with human participation comply with the ethical standards of the 1964 Helsinki Declaration and its subsequent amendments or with comparable ethical standards. Informed voluntary consent was received from each participant included in the study.

CONFLICT OF INTEREST

The authors declare that they have no conflicts of interest.

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Translated by A. Nikol’skii

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Kistenev, Y.V., Teteneva, A.V., Sorokina, T.V. et al. Diagnosis of Diabetes Based on Analysis of Exhaled Air by Terahertz Spectroscopy and Machine Learning. Opt. Spectrosc. 128, 809–814 (2020). https://doi.org/10.1134/S0030400X20060090

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