Classification of tic disorders based on functional MRI by machine learning: a study protocol.

ABSTRACT:

Introduction

Tic disorder (TD) is a common neurodevelopmental disorder in children, and it can be categorised into three subtypes: provisional tic disorder (PTD), chronic motor or vocal TD (CMT or CVT), and Tourette syndrome (TS). An early diagnostic classification among these subtypes is not possible based on a new-onset tic symptom. Machine learning tools have been widely used for early diagnostic classification based on functional MRI (fMRI). However, few machine learning models have been built for the diagnostic classification of patients with TD. Therefore, in the present study, we will provide a study protocol that uses the machine learning model to make early classifications of the three different types of TD.

Methods and analysis

We planned to recruit 200 children ag

SUBMITTER: Wang F 

PROVIDER: S-EPMC9114957 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature