Efficiency of Artificial Intelligence Methods for Hearing Loss Type Classification: An Evaluation
Authors
Michał Kassjański
Department of Geoinformatics, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk, Poland
Marcin Kulawiak
Department of Geoinformatics, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk, Poland
Tomasz Przewoźny
Department of Otolaryngology, Medical University of Gdansk, Gdansk, Poland
Dmitry Tretiakow
Department of Otolaryngology, the Nicolaus Copernicus Hospital in Gdansk, Copernicus Healthcare Entity, Gdansk, Poland
Jagoda Kuryłowicz
Department of Otolaryngology, Medical University of Gdansk, Gdansk, Poland
Andrzej Molisz
Department of Otolaryngology, Medical University of Gdansk, Gdansk, Poland
Krzysztof Koźmiński
Student’s Scientific Circle of Otolaryngology, Medical University of Gdańsk, Gdansk, Poland
Aleksandra Kwaśniewska
Department of Otolaryngology, Laryngological Oncology and Maxillofacial Surgery, University Hospital No. 2, Bydgoszcz, Poland
Paulina Mierzwińska‑Dolny
paulinamierzwinska@gumed.edu.pl
Student’s Scientific Circle of Otolaryngology, Medical University of Gdańsk, Gdansk, Poland
Miłosz Grono
Student’s Scientific Circle of Otolaryngology, Medical University of Gdańsk, Gdansk, Poland
Language: English
Page range: 28 - 38
Submitted on: Dec 9, 2023
Accepted on: Mar 26, 2024
Published on: Sep 12, 2024
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
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© 2024 Michał Kassjański, Marcin Kulawiak, Tomasz Przewoźny, Dmitry Tretiakow, Jagoda Kuryłowicz, Andrzej Molisz, Krzysztof Koźmiński, Aleksandra Kwaśniewska, Paulina Mierzwińska‑Dolny, Miłosz Grono, published by Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.