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OBJECTIVE: To use machine learning in the form of a deep neural network to objectively classify paired auditory brainstem response waveforms into either: 'clear response', 'inconclusive' or 'response absent'. DESIGN: A deep convolutional neural network was trained and fine-tuned using stratified 10-fold cross-validation on 190 paired ABR waveforms. The final model was evaluated on a test set of 42 paired waveforms. STUDY SAMPLE: The full dataset comprised 232 paired ABR waveforms recorded from eight normal-hearing individuals. The dataset was obtained from the PhysioBank database. The paired waveforms were independently labelled by two audiological scientists in order to train and evaluate the network's performance. RESULTS: The trained neural network was able to classify paired ABR waveforms with 92.9% accuracy. The sensitivity and specificity were 92.9% and 96.4% respectively. CONCLUSIONS: This neural network may have clinical utility in assisting clinicians with waveform classification for the purpose of hearing threshold estimation. Further evaluation on a large clinically-obtained dataset would provide further validation with regards to the clinical potential of the neural network in diagnostic adult testing, newborn testing and in automated newborn hearing screening.

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ObjectiveTo assess, using standardised tools, the quality and readability of online tinnitus information that patients are likely to access.MethodsA standardised review was conducted of websites relating to tinnitus and its management. Each website was scored using the DISCERN instrument and the Flesch Reading Ease scale.ResultsTwenty-seven unique websites were evaluated. The mean DISCERN score of the websites was 34.5 out of 80 (standard deviation = 11.2). This would be considered ‘fair’ in quality. Variability in DISCERN score between websites was high (range, 15–57: ‘poor’ to ‘very good’). Website readability was poor, with a mean Flesch Reading Ease score of 52.6 (standard deviation = 7.7); this would be considered ‘difficult’ to read.ConclusionIn general, the quality of tinnitus websites is fair and the readability is poor, with substantial variability in quality between websites. The Action on Hearing Loss and the British Tinnitus Association websites were identified as providing the highest quality information.