학술논문
Machine Learning Approaches in Study of Multiple Sclerosis Disease Through Magnetic Resonance Images
Document Type
article
Source
Frontiers in Immunology, Vol 12 (2021)
Subject
Language
English
ISSN
1664-3224
Abstract
Multiple sclerosis (MS) is one of the most common autoimmune diseases which is commonly diagnosed and monitored using magnetic resonance imaging (MRI) with a combination of clinical manifestations. The purpose of this review is to highlight the main applications of Machine Learning (ML) models and their performance in the MS field using MRI. We reviewed the articles of the last decade and grouped them based on the applications of ML in MS using MRI data into four categories: 1) Automated diagnosis of MS, 2) Prediction of MS disease progression, 3) Differentiation of MS stages, 4) Differentiation of MS from similar disorders.