250 related articles for article (PubMed ID: 32199461)
1. Machine learning analysis of motor evoked potential time series to predict disability progression in multiple sclerosis.
Yperman J; Becker T; Valkenborg D; Popescu V; Hellings N; Wijmeersch BV; Peeters LM
BMC Neurol; 2020 Mar; 20(1):105. PubMed ID: 32199461
[TBL] [Abstract][Full Text] [Related]
2. Monitoring multiple sclerosis by multimodal evoked potentials: Numerically versus ordinally scaled scoring systems.
Schlaeger R; Hardmeier M; D'Souza M; Grize L; Schindler C; Kappos L; Fuhr P
Clin Neurophysiol; 2016 Mar; 127(3):1864-71. PubMed ID: 26754876
[TBL] [Abstract][Full Text] [Related]
3. Multimodal evoked potentials for functional quantification and prognosis in multiple sclerosis.
Giffroy X; Maes N; Albert A; Maquet P; Crielaard JM; Dive D
BMC Neurol; 2016 Jun; 16():83. PubMed ID: 27245221
[TBL] [Abstract][Full Text] [Related]
4. Combined visual and motor evoked potentials predict multiple sclerosis disability after 20 years.
Schlaeger R; Schindler C; Grize L; Dellas S; Radue EW; Kappos L; Fuhr P
Mult Scler; 2014 Sep; 20(10):1348-54. PubMed ID: 24574192
[TBL] [Abstract][Full Text] [Related]
5. Prognostic value of multimodal evoked potentials in multiple sclerosis: the EP score.
Invernizzi P; Bertolasi L; Bianchi MR; Turatti M; Gajofatto A; Benedetti MD
J Neurol; 2011 Nov; 258(11):1933-9. PubMed ID: 21479648
[TBL] [Abstract][Full Text] [Related]
6. Explainable machine learning models based on multimodal time-series data for the early detection of Parkinson's disease.
Junaid M; Ali S; Eid F; El-Sappagh S; Abuhmed T
Comput Methods Programs Biomed; 2023 Jun; 234():107495. PubMed ID: 37003039
[TBL] [Abstract][Full Text] [Related]
7. The Use of Motor-Evoked Potentials in Clinical Trials in Multiple Sclerosis.
Fernández V
J Clin Neurophysiol; 2021 May; 38(3):166-170. PubMed ID: 33958566
[TBL] [Abstract][Full Text] [Related]
8. Prediction of long-term disability in multiple sclerosis.
Schlaeger R; D'Souza M; Schindler C; Grize L; Dellas S; Radue EW; Kappos L; Fuhr P
Mult Scler; 2012 Jan; 18(1):31-8. PubMed ID: 21868486
[TBL] [Abstract][Full Text] [Related]
9. Early abnormalities of evoked potentials and future disability in patients with multiple sclerosis.
Kallmann BA; Fackelmann S; Toyka KV; Rieckmann P; Reiners K
Mult Scler; 2006 Feb; 12(1):58-65. PubMed ID: 16459720
[TBL] [Abstract][Full Text] [Related]
10. Motor evoked potentials and disability in secondary progressive multiple sclerosis.
Facchetti D; Mai R; Micheli A; Marcianó N; Capra R; Gasparotti R; Poloni M
Can J Neurol Sci; 1997 Nov; 24(4):332-7. PubMed ID: 9398981
[TBL] [Abstract][Full Text] [Related]
11. Do evoked potentials contribute to the functional follow-up and clinical prognosis of multiple sclerosis?
Giffroy X; Maes N; Albert A; Maquet P; Crielaard JM; Dive D
Acta Neurol Belg; 2017 Mar; 117(1):53-59. PubMed ID: 27194163
[TBL] [Abstract][Full Text] [Related]
12. Correlation between disability and transcranial magnetic stimulation abnormalities in patients with multiple sclerosis.
Kale N; Agaoglu J; Onder G; Tanik O
J Clin Neurosci; 2009 Nov; 16(11):1439-42. PubMed ID: 19695880
[TBL] [Abstract][Full Text] [Related]
13. Combined evoked potentials as markers and predictors of disability in early multiple sclerosis.
Schlaeger R; D'Souza M; Schindler C; Grize L; Kappos L; Fuhr P
Clin Neurophysiol; 2012 Feb; 123(2):406-10. PubMed ID: 21778106
[TBL] [Abstract][Full Text] [Related]
14. Statistical characterization and classification of colon microarray gene expression data using multiple machine learning paradigms.
Maniruzzaman M; Jahanur Rahman M; Ahammed B; Abedin MM; Suri HS; Biswas M; El-Baz A; Bangeas P; Tsoulfas G; Suri JS
Comput Methods Programs Biomed; 2019 Jul; 176():173-193. PubMed ID: 31200905
[TBL] [Abstract][Full Text] [Related]
15. Machine learning classifier to identify clinical and radiological features relevant to disability progression in multiple sclerosis.
Tommasin S; Cocozza S; Taloni A; Giannì C; Petsas N; Pontillo G; Petracca M; Ruggieri S; De Giglio L; Pozzilli C; Brunetti A; Pantano P
J Neurol; 2021 Dec; 268(12):4834-4845. PubMed ID: 33970338
[TBL] [Abstract][Full Text] [Related]
16. Evoked potentials can predict future disability in people with clinically isolated syndrome.
Crnošija L; Gabelić T; Barun B; Adamec I; Krbot Skorić M; Habek M
Eur J Neurol; 2020 Mar; 27(3):437-444. PubMed ID: 31574192
[TBL] [Abstract][Full Text] [Related]
17. Computational classifiers for predicting the short-term course of Multiple sclerosis.
Bejarano B; Bianco M; Gonzalez-Moron D; Sepulcre J; Goñi J; Arcocha J; Soto O; Del Carro U; Comi G; Leocani L; Villoslada P
BMC Neurol; 2011 Jun; 11():67. PubMed ID: 21649880
[TBL] [Abstract][Full Text] [Related]
18. Deciphering the Morphology of Motor Evoked Potentials.
Yperman J; Becker T; Valkenborg D; Hellings N; Cambron M; Dive D; Laureys G; Popescu V; Van Wijmeersch B; Peeters LM
Front Neuroinform; 2020; 14():28. PubMed ID: 32765249
[TBL] [Abstract][Full Text] [Related]
19. [Electrophysiological diagnosis of multiple sclerosis].
Inamizu S; Tobimatsu S
Nihon Rinsho; 2014 Nov; 72(11):1983-8. PubMed ID: 25518381
[TBL] [Abstract][Full Text] [Related]
20. An investigation of machine learning methods in delta-radiomics feature analysis.
Chang Y; Lafata K; Sun W; Wang C; Chang Z; Kirkpatrick JP; Yin FF
PLoS One; 2019; 14(12):e0226348. PubMed ID: 31834910
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
