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[Diagnosis of benign laryngeal tumors using neural network]. / Diagnostika dobrokachestvennykh novoobrazovanii gortani s primeneniem neiroseti.
Kryukov, A I; Sudarev, P A; Romanenko, S G; Kurbanova, D I; Lesogorova, E V; Krasilnikova, E N; Pavlikhin, O G; Ivanova, A A; Osadchiy, A P; Shevyrina, N G.
Afiliación
  • Kryukov AI; Sverzhevsky Research Clinical Institute of Otorhinolaryngology, Moscow, Russia.
  • Sudarev PA; Sverzhevsky Research Clinical Institute of Otorhinolaryngology, Moscow, Russia.
  • Romanenko SG; Sverzhevsky Research Clinical Institute of Otorhinolaryngology, Moscow, Russia.
  • Kurbanova DI; Sverzhevsky Research Clinical Institute of Otorhinolaryngology, Moscow, Russia.
  • Lesogorova EV; Sverzhevsky Research Clinical Institute of Otorhinolaryngology, Moscow, Russia.
  • Krasilnikova EN; Sverzhevsky Research Clinical Institute of Otorhinolaryngology, Moscow, Russia.
  • Pavlikhin OG; Sverzhevsky Research Clinical Institute of Otorhinolaryngology, Moscow, Russia.
  • Ivanova AA; Rubedo LLC, Moscow, Russia.
  • Osadchiy AP; Rubedo LLC, Moscow, Russia.
  • Shevyrina NG; Rubedo LLC, Moscow, Russia.
Vestn Otorinolaringol ; 89(3): 24-28, 2024.
Article en Ru | MEDLINE | ID: mdl-39104269
ABSTRACT
The article describes our experience in developing and training an artificial neural network based on artificial intelligence algorithms for recognizing the characteristic features of benign laryngeal tumors and variants of the norm of the larynx based on the analysis of laryngoscopy pictures obtained during the examination of patients. During the preparation of data for training the neural network, a dataset was collected, labeled and loaded, consisting of 1471 images of the larynx in digital formats (jpg, bmp). Next, the neural network was trained and tested in order to recognize images of the norm and neoplasms of the larynx. The developed and trained artificial neural network demonstrated an accuracy of 86% in recognizing of benign laryngeal tumors and variants of the norm of the larynx. The proposed technology can be further used in practical healthcare to control and improve the quality of diagnosis of laryngeal pathologies.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias Laríngeas / Redes Neurales de la Computación / Laringoscopía Límite: Humans / Male Idioma: Ru Revista: Vestn Otorinolaringol Año: 2024 Tipo del documento: Article País de afiliación: Rusia

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias Laríngeas / Redes Neurales de la Computación / Laringoscopía Límite: Humans / Male Idioma: Ru Revista: Vestn Otorinolaringol Año: 2024 Tipo del documento: Article País de afiliación: Rusia