Diagnosis of multiple sclerosis using optical coherence tomography supported by explainable artificial intelligence
Author:
Funder
Carlos III Health Research Institute
Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41433-024-02933-5.pdf
Reference26 articles.
1. Thompson AJ, Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol [Internet]. 2018;17:162–73. https://linkinghub.elsevier.com/retrieve/pii/S1474442217304702.
2. van der Vuurst de Vries RM, Mescheriakova JY, Wong YYM, Runia TF, Jafari N, Samijn JP, et al. Application of the 2017 revised Mcdonald criteria for multiple sclerosis to patients with a typical clinically isolated syndrome. JAMA Neurol. 2018;75:1392.
3. Gaitán MI, Sanchez M, Farez MF, Fiol MP, Ysrraelit MC, Solomon AJ, et al. The frequency and characteristics of multiple sclerosis misdiagnosis in Latin America: A referral center study in Buenos Aires, Argentina. Mult Scler J. 2022;28:1373–81.
4. Petzold A, Balcer LJ, Calabresi PA, Costello F, Frohman TC, Frohman EM, et al. Retinal layer segmentation in multiple sclerosis: a systematic review and meta-analysis. Lancet Neurol [Internet]. 2017;16:797–812. https://linkinghub.elsevier.com/retrieve/pii/S1474442217302788.
5. Ortiz M, Mallen V, Boquete L, Sánchez-Morla EM, Cordón B, Vilades E, et al. Diagnosis of multiple sclerosis using optical coherence tomography supported by artificial intelligence. Mult Scler Relat Disord. 2023;74:104725.
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