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Войти в исследования The Journal of laryngology and otology · 2024
Predicting noise-induced hearing loss with machine learning: the influence of tinnitus as a predictive factor.
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Soylemez Emre, Avci Isa, Yildirim Elif, Karaboya Engin, Yilmaz Nihat, Ertugrul Süha, Tokgoz-Yilmaz Suna
Аннотация
OBJECTIVES: This study aimed to determine which machine learning model is most suitable for predicting noise-induced hearing loss and the effect of tinnitus on the models' accuracy.
METHODS: Two hundred workers employed in a metal industry were selected for this study and tested using pure tone audiometry. Their occupational exposure histories were collected, analysed and used to create a dataset. Eighty per cent of the data collected was used to train six machine learning models and the remaining 20 per cent was used to test the models.
RESULTS: Eight workers (40.5 per cent) had bilaterally normal hearing and 119 (59.5 per cent) had hearing loss. Tinnitus was the second most important indicator after age for noise-induced hearing loss. The support vector machine was the best-performing algorithm, with 90 per cent accuracy, 91 per cent F1 score, 95 per cent precision and 88 per cent recall.
CONCLUSION: The use of tinnitus as a risk factor in the support vector machine model may increase the success of occupational health and safety programmes.
METHODS: Two hundred workers employed in a metal industry were selected for this study and tested using pure tone audiometry. Their occupational exposure histories were collected, analysed and used to create a dataset. Eighty per cent of the data collected was used to train six machine learning models and the remaining 20 per cent was used to test the models.
RESULTS: Eight workers (40.5 per cent) had bilaterally normal hearing and 119 (59.5 per cent) had hearing loss. Tinnitus was the second most important indicator after age for noise-induced hearing loss. The support vector machine was the best-performing algorithm, with 90 per cent accuracy, 91 per cent F1 score, 95 per cent precision and 88 per cent recall.
CONCLUSION: The use of tinnitus as a risk factor in the support vector machine model may increase the success of occupational health and safety programmes.