Prediction of hearing loss through application of Deep Neural Network
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S. Calabrese, E. Donati, and C. Chousidis, "Prediction of hearing loss through application of Deep Neural Network," Paper 10373, (2020 May.). doi:
S. Calabrese, E. Donati, and C. Chousidis, "Prediction of hearing loss through application of Deep Neural Network," Paper 10373, (2020 May.). doi:
Abstract: This paper describes a neural network designed to provide aid in the preventive diagnosis of hearing loss issues. Hearing loss is a widely widespread disability affecting millions of people worldwide. An anonymous dataset is used to train a neural network to evaluate hearing loss in prevention and early diagnosis with the aim of supporting health care by optimising time and cost. The system is tested using a second set of data and results in a correct evaluation of whether the patient is affected by hearing loss or not.
@article{calabrese2020prediction,
author={calabrese, samuele and donati, eugenio and chousidis, christos},
journal={journal of the audio engineering society},
title={prediction of hearing loss through application of deep neural network},
year={2020},
volume={},
number={},
pages={},
doi={},
month={may},}
@article{calabrese2020prediction,
author={calabrese, samuele and donati, eugenio and chousidis, christos},
journal={journal of the audio engineering society},
title={prediction of hearing loss through application of deep neural network},
year={2020},
volume={},
number={},
pages={},
doi={},
month={may},
abstract={this paper describes a neural network designed to provide aid in the preventive diagnosis of hearing loss issues. hearing loss is a widely widespread disability affecting millions of people worldwide. an anonymous dataset is used to train a neural network to evaluate hearing loss in prevention and early diagnosis with the aim of supporting health care by optimising time and cost. the system is tested using a second set of data and results in a correct evaluation of whether the patient is affected by hearing loss or not.},}
TY - paper
TI - Prediction of hearing loss through application of Deep Neural Network
SP -
EP -
AU - Calabrese, Samuele
AU - Donati, Eugenio
AU - Chousidis, Christos
PY - 2020
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2020
TY - paper
TI - Prediction of hearing loss through application of Deep Neural Network
SP -
EP -
AU - Calabrese, Samuele
AU - Donati, Eugenio
AU - Chousidis, Christos
PY - 2020
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2020
AB - This paper describes a neural network designed to provide aid in the preventive diagnosis of hearing loss issues. Hearing loss is a widely widespread disability affecting millions of people worldwide. An anonymous dataset is used to train a neural network to evaluate hearing loss in prevention and early diagnosis with the aim of supporting health care by optimising time and cost. The system is tested using a second set of data and results in a correct evaluation of whether the patient is affected by hearing loss or not.
This paper describes a neural network designed to provide aid in the preventive diagnosis of hearing loss issues. Hearing loss is a widely widespread disability affecting millions of people worldwide. An anonymous dataset is used to train a neural network to evaluate hearing loss in prevention and early diagnosis with the aim of supporting health care by optimising time and cost. The system is tested using a second set of data and results in a correct evaluation of whether the patient is affected by hearing loss or not.
Authors:
Calabrese, Samuele; Donati, Eugenio; Chousidis, Christos
Affiliation:
University of West London
AES Convention:
148 (May 2020)
Paper Number:
10373
Publication Date:
May 28, 2020Import into BibTeX
Subject:
Signal Processing
Permalink:
http://www.aes.org/e-lib/browse.cfm?elib=20790