R.V. Agandeev1, I.A. Pavleev2, V.Sh. Yabbarova3, V.Yu. Leushin4
1,3 National Innovation Company LLC (Moscow, Russia)
2,4 Krinos LLC (Moscow, Russia)
2 Lomonosov Moscow State University (Moscow, Russia)
4 Bauman Moscow State Technical University (National Research University) (Moscow, Russia)
The article "Intelligent analysis of data arrays in the process of diagnosing sensorineural hearing loss" discusses the use of artificial intelligence and machine learning methods for the diagnosis of sensorineural hearing loss.
Sensorineural hearing loss is a hearing disorder that can be caused by various factors, such as genetic predispositions, infections, injuries, and others. Diagnosis of this disease is based on the analysis of audiometric data obtained during special tests.
\The article describes a data mining technique that allows you to automatically process large amounts of information and identify hidden patterns. To do this, various machine learning algorithms are used, such as neural networks, the support vector machine method and decision trees.
The results of the study showed that data mining can be an effective tool for the diagnosis of sensorineural hearing loss. Automatic data processing allows you to identify hidden patterns and determine the presence or absence of a disease with high accuracy.
Thus, the use of artificial intelligence and machine learning methods in the diagnosis of sensorineural hearing loss can significantly improve the accuracy of diagnosis and help in choosing the optimal treatment for patients.
The work was carried out with the support of the "Fund for Assistance to the Development of Small Forms of Enterprises in the Scientific and Technical Sphere" (project No. 86GRCEIIS12-D7/79060).
Agandeev R.V., Pavleev I.A., Yabbarova V.Sh., Leushin V.Yu. Intelligent analysis of data arrays in the process of diagnostics of sensorineural hearing loss. Nanotechnology: development and applications – XXI century. 2023. V. 15. № 3. P. 57–63. DOI: https://doi.org/10.18127/j22250980-202303-06 (in Russian)
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