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Applying Machine Learning Models to Predict Occupational Noise-Induced Hearing Loss: A Systematic Review and Meta-analysis
- Truvace record
- TRV-2026-2713raw data (JSON)
- Version
- v1Published
- First published
- Evidence type
- Systematic review or meta-analysis
- Sources
- 1 sourcePeer-reviewed
- sha256
- 1c20cbf7b01b…check it
OBJECTIVES: To map and critically appraise prediction models for occupational noise-induced hearing loss (ONIHL) using machine learning (ML) approaches and to evaluate reporting quality and risk of bias. METHODS: Seven databases were systematically searched. Reporting quality was assessed using the TRIPOD-AI checklist, and risk of bias and applicability were evaluated using the PROBAST tool. A meta-analysis was performed to evaluate ML model performance for predicting ONIHL using the area under the curve (AUC),…
The problem
A systematic review of 16 studies on machine learning prediction of occupational noise-induced hearing loss found 56% at high risk of bias, none externally validated, and a pooled AUC of 0.788 for ML models versus 0.811 for logistic regression.
What this doesn’t fix
Heterogeneity was not fully explained by subgroup analyses, the number of studies per algorithm was small, and no included study was externally validated.
Sources
1 on file- Noise and Healthdoi:10.4103/nah.nah_11_26
What the review found when it combined the studies
These are the review’s own pooled results, copied from its abstract. Truvace did not recalculate them.
Discrimination of machine learning models predicting occupational noise-induced hearing loss
AUC 0.788 (95% CI 0.761 to 0.813)
16 studies · 29,094 people
The review’s own words
The pooled AUC was 0.788 (95% CI: 0.761–0.813).
Discrimination of k-nearest neighbours models predicting occupational noise-induced hearing loss
AUC 0.837 (95% CI 0.785 to 0.878)
16 studies · 29,094 people
The review’s own words
KNN followed (AUC = 0.837; 95% CI: 0.785–0.878) with negligible heterogeneity ( I 2 = 3.6%).
Discrimination of logistic regression models predicting occupational noise-induced hearing loss
AUC 0.811 (95% CI 0.743 to 0.865)
16 studies · 29,094 people
The review’s own words
The pooled AUC was 0.811 (95% CI: 0.743–0.865).
Code checks every number above against the review’s text before it is shown. The short labels are an AI model’s reading of that text, so the review’s own sentence sits under each one. A pooled figure is only as strong as the studies behind it. How Truvace uses pooled results
Cite this record
v1Truvace Impact Record TRV-2026-2713, v1: “Applying Machine Learning Models to Predict Occupational Noise-Induced Hearing Loss: A Systematic Review and Meta-analysis.” Truvace, 2026-11-12. /record/TRV-2026-2713 (accessed on the day you copy it). sha256 1c20cbf7b01b79bc…
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