A semi-supervised Support Vector Machine model for predicting the language outcomes following cochlear implantation based on pre-implant brain fMRI imaging

Brain and Behavior
Lirong TanLong J Lu

Abstract

We developed a machine learning model to predict whether or not a cochlear implant (CI) candidate will develop effective language skills within 2 years after the CI surgery by using the pre-implant brain fMRI data from the candidate. The language performance was measured 2 years after the CI surgery by the Clinical Evaluation of Language Fundamentals-Preschool, Second Edition (CELF-P2). Based on the CELF-P2 scores, the CI recipients were designated as either effective or ineffective CI users. For feature extraction from the fMRI data, we constructed contrast maps using the general linear model, and then utilized the Bag-of-Words (BoW) approach that we previously published to convert the contrast maps into feature vectors. We trained both supervised models and semi-supervised models to classify CI users as effective or ineffective. Compared with the conventional feature extraction approach, which used each single voxel as a feature, our BoW approach gave rise to much better performance for the classification of effective versus ineffective CI users. The semi-supervised model with the feature set extracted by the BoW approach from the contrast of speech versus silence achieved a leave-one-out cross-validation AUC as high as 0.97....Continue Reading

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Citations

Jan 18, 2018·Proceedings of the National Academy of Sciences of the United States of America·Gangyi FengPatrick C M Wong
Sep 22, 2018·Otology & Neurotology : Official Publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology·Yan ZouHui Ma
Oct 24, 2019·Otology & Neurotology : Official Publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology·Matthew G CrowsonTimothy C Y Chan
Jul 10, 2019·Disability and Rehabilitation. Assistive Technology·Emily A KringleLauren Terhorst
Jul 8, 2020·Clinical and Experimental Otorhinolaryngology·Bayu Adhi TamaSoo Whan Kim
Sep 17, 2021·Otology & Neurotology : Official Publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology·Hajime KoyamaKatsumi Doi

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Methods Mentioned

BETA
cochlear implant
sedation
feature extraction

Software Mentioned

SVM
R package pROC
MATLAB
xjView
SVM light package
SPM8
pROC

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