ArticleLa Medicina del lavoro2022
Predicting and classifying hearing loss in sailors working on speed vessels using neural networks: a field study.
Article in La Medicina del lavoro, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- A Scoping Review on Occupational Noise Mitigation Strategies and Recommendations for Sustainable Ship Operations.International journal of environmental research and public health · 2024Article
- Exploring the influence of music on cognitive performance in female assembly line workers at a medical device manufacturing unit.PloS one · 2024Article
- Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNoise-induced hearing loss (NIHL) is one of the main risk factors affecting people's health and wellbeing in the workplace. Analysing NIHL and consequently controlling the causing factors can significantly affect the improvement of working environments. Methods: One hundred and twelve male sailors participated in this study. They were classified into three groups depending on occupational noise exposure: (A) none, i.e., sound pressure level (SPL) lower than 70dBA, (B) exposed to SPL in the range of 70-85dBA, and (C) exposed to SPL exceeding 80dBA. In a first phase, hearing loss shaping risk factors were identified and analysed, including hearing loss in different frequencies, age, work experience, sound pressure level (SPL), marital status, and systolic and diastolic blood pressure. Then, neural networks were trained to predict the hearing loss changes of personnel and used to determine the weight of hearing loss factors. Finally, the accuracy of predicting models was calculated relying on Bayesian statistics. Results and conclusion: In the present study using neural networks, five models were developed. Their accuracy ranged from 92% to 100%. The frequencies of 4000Hz and 2000Hz showed the strongest association with the hearing loss of the sailors. Also, including systolic and diastolic blood pressure did not have any impact on predicted hearing loss, indicating that SPL was poorly correlated with extra-auditory effects.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.