Machine learning in diagnosis and disability prediction of multiple sclerosis using optical coherence tomography-Reference-Cited by-同舟云学术

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Machine learning in diagnosis and disability prediction of multiple sclerosis using optical coherence tomography

Published:2021-06 Issue: Volume:133 Page:104416
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Montolío Alberto^ORCID,Martín-Gallego Alejandro,Cegoñino José,Orduna Elvira^ORCID,Vilades Elisa,Garcia-Martin Elena,Palomar Amaya Pérez del

Funder

Instituto de Salud Carlos III

Ministerio de Ciencia, Innovación y Universidades

Ministerio de Economía y Competitividad

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference64 articles.

1. Axonal damage in acute multiple sclerosis lesions;Ferguson;Brain,1997

2. Chronic demyelination exacerbates neuroaxonal loss in patients with MS with unilateral optic neuritis;You;Neurol. Neuroimmunol. Neuroinflammation.,2020

3. Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria,” Ann;Polman;Neurol.,2005

4. Neural networks to identify multiple sclerosis with optical coherence tomography;Garcia-Martin;Acta Ophthalmol.,2013

5. An effective method for computerized prediction and segmentation of multiple sclerosis lesions in brain MRI;Roy;Comput. Methods Progr. Biomed.,2017

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