Machine learning models can predict standard Bisgaard audiogram types from calibration-independent ACALOS loudness data with reasonable accuracy despite substantial class overlap.
However, PCA projections were insufficient for classifying six groups, underscoring the complexity of the data and the limits of unsupervised clustering for this task
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Standard audiogram classification from loudness scaling data using unsupervised, supervised, and explainable machine learning techniques
Machine learning models can predict standard Bisgaard audiogram types from calibration-independent ACALOS loudness data with reasonable accuracy despite substantial class overlap.