Discover the newest research about AI innovations in π Audiology.
AI in Thyroid Ultrasound Training: 70% Accuracy Achieved! π€π Automated assessments enhance skill evaluation in medical simulations.
DNN noise reduction boosts speech recognition in bimodal CI users by 19% in noise. ππ
AI enhances laryngeal endoscopy image analysis, achieving segmentation quality comparable to human raters. π¦π
Machine learning predicts occupational noise-induced hearing loss using blood indicators. AUC 0.942, sensitivity 0.875, specificity 0.936. ππ
Deep learning enhances pediatric audiometry accuracy: sensitivity up to 0.943, specificity 0.947. Real-time monitoring improves hearing assessments. ππΆ
New study reveals TUG test with IMU sensors effectively detects vestibular impairments. Sensitivity up to 95%! π§ βοΈ
New tech aids hearing loss research! 𦻠FAVE estimates thresholds from handwritten audiograms, enhancing data accessibility. π
Exploring the fusion of machine learning and physics in physiology. π§ π¬ Insights from a recent PubMed article.
Exploring AI in language disorder detection π€π: Recent advances enhance assessment efficiency for childrenβs language disorders.
Exploring glottis segmentation’s challenges and advancements in voice physiology research. π€π Key insights from a recent PubMed article. π
