Meeting Banner
Abstract #4808

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

Xiao-Min Xu1 and Yu-Chen Chen1
1Radiology, Nanjing First Hospital, Nanjing, China

Synopsis

Keywords: Head & Neck/ENT, fMRI (resting state)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.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.

Keywords