The diagnostic performance of AI-based algorithms to discriminate between NMOSD and MS using MRI features: A systematic review and meta-analysis-Reference-Cited by-同舟云学术

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The diagnostic performance of AI-based algorithms to discriminate between NMOSD and MS using MRI features: A systematic review and meta-analysis

Published:2024-07 Issue: Volume:87 Page:105682
ISSN:2211-0348
Container-title:Multiple Sclerosis and Related Disorders
language:en
Short-container-title:Multiple Sclerosis and Related Disorders

Author:

Etemadifar Masoud,Norouzi Mahdi^ORCID,Alaei Seyyed-Ali,Karimi Raheleh,Salari Mehri

Publisher

Elsevier BV

Reference39 articles.

1. Brain and spinal cord lesion criteria distinguishes AQP4-positive neuromyelitis optica and MOG-positive disease from multiple sclerosis;Bensi;Mult. Scler. Relat. Disord.,2018

2. Application of deep-learning to NMOSD and unclassified seronegative patients;Cacciaguerra;Mult. Sclero. J.,2020

3. Brain and spinal MRI features distinguishing MS from different AQP4 antibody serostatus NMOSD at disease onset in a cohort of Latin American patients;Carnero Contentti;Mult. Scler. Houndmill. Basingstoke Engl.,2020

4. MRI patterns distinguish AQP4 antibody positive neuromyelitis optica spectrum disorder from multiple sclerosis;Clarke;Front. Neurol.,2021

5. Clinical and MRI measures to identify non-acute MOG-antibody disease in adults;Cortese;Brain,2023

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1. Use of ultrasound imaging Omics in predicting molecular typing and assessing the risk of postoperative recurrence in breast cancer;BMC Women's Health;2024-07-02

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