AIMC Topic: Hearing Loss, Noise-Induced

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Machine Learning Models Can Predict Tinnitus and Noise-Induced Hearing Loss.

Ear and hearing
OBJECTIVES: Despite the extensive use of machine learning (ML) models in health sciences for outcome prediction and condition classification, their application in differentiating various types of auditory disorders remains limited. This study aimed t...

Comparison between logistic regression and machine learning algorithms on prediction of noise-induced hearing loss and investigation of SNP loci.

Scientific reports
To compare the comprehensive performance of conventional logistic regression (LR) and seven machine learning (ML) algorithms in Noise-Induced Hearing Loss (NIHL) prediction, and to investigate the single nucleotide polymorphism (SNP) loci significant...

Applying machine learning algorithms to explore the impact of combined noise and dust on hearing loss in occupationally exposed populations.

Scientific reports
This study aimed to explore the combined impacts of occupational noise and dust on hearing and extra-auditory functions and identify associated risk factors via machine learning techniques. Data from 14,145 workers (627 with occupational noise-induce...

Research on noise-induced hearing loss based on functional and structural MRI using machine learning methods.

Scientific reports
Noise-induced hearing loss (NIHL) is a common occupational condition. The aim of this study was to develop a classification model for NIHL on the basis of both functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sM...

Hearing loss prediction equation for Iranian truck drivers using neural network algorithm.

Work (Reading, Mass.)
BACKGROUND:  Given the high prevalence of hearing loss among truck drivers, using artificial neural networks (ANNs) to predict and detect contributing factors early can aid managers significantly.

Predicting noise-induced hearing loss with machine learning: the influence of tinnitus as a predictive factor.

The Journal of laryngology and otology
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.

Noise exposure during robot-assisted total knee arthroplasty.

Archives of orthopaedic and trauma surgery
The aim of the study was to examine the noise exposure for operating theater staff during total knee arthroplasty (TKA) with three different robot systems. There is already evidence that noise exposure during TKA performed manually exceeds recommende...

Contributions and limitations of using machine learning to predict noise-induced hearing loss.

International archives of occupational and environmental health
PURPOSE: Noise-induced hearing loss (NIHL) is a global issue that impacts people's life and health. The current review aims to clarify the contributions and limitations of applying machine learning (ML) to predict NIHL by analyzing the performance of...