Machine learning for detecting sensorineural hearing loss utilizing functional imaging with a combination of static and dynamic brain features

Alterations of static and dynamic brain function have been found in sensorineural hearing loss (SNHL). The combination of data-driven machine learning based classifiers and multiple imaging features can identify SNHL and healthy controls automatically. The spearman rank correlation with radial basis functional kernel support vector machine (SVM) and sigmoid SVM provides promising neural biomarkers for clinical classifier of SNHL.