Prediction of Vestibular Dysfunction by Applying Machine Learning Algorithms to Postural Instability

Objective: To evaluate various machine learning algorithms in predicting peripheral vestibular dysfunction using the dataset of the center of pressure (COP) sway during foam posturography measured from patients with dizziness.Study Design: Retrospective study.Setting: Tertiary referral center.Patien...

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Detalhes bibliográficos

Principais autores:	Teru Kamogashira, Chisato Fujimoto, Makoto Kinoshita, Yayoi Kikkawa, Tatsuya Yamasoba, Shinichi Iwasaki
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2020-02-01
coleção:	Frontiers in Neurology
Assuntos:	posturography tests machine learning (artificial intelligence) vestibular dysfunction Gradient Boosting Decision Tree (GBDT) hyperparameter
Acesso em linha:	https://www.frontiersin.org/article/10.3389/fneur.2020.00007/full
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