06Nov 2024
Automated ML Audiometry Matches Traditional Tests in Accuracy

Automated ML Audiometry Matches Traditional Tests in Accuracy

The study developed a machine learning (ML)-based approach for fully automated bone conduction (BC) audiometry to improve efficiency and precision in hearing assessments. Across three studies, the ML-audiometry system was evaluated for occlusion effects, contralateral masking, and forehead-mastoid corrections. Comparisons of automated ML audiometry with traditional manual BC audiometry showed no significant performance differences, and high test-retest reliability was demonstrated. The results indicate that ML audiometry performs on par with conventional methods in assessing auditory function, offering a reliable, automated solution for normal-hearing and hearing-impaired individuals with mild to severe hearing loss.

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