Machine learning approach defines immune response during met-enkephalin immunotherapy in multiple sclerosis and optic neuritis. (CROSBI ID 466556)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Štambuk, Nikola ; Mašić, Nikola ; Brinar, Vesna ; Trbojević-Čepe, Milica ; Štambuk, Vjera ; Rabatić, Sabina ; Marotti, Tanja ; Šverko, Višnja ; Marušić-Della Marina, Branka ; Brzović, Zdravko ; Zurak, Niko ; Svoboda Beusan, Ivna ; Mažuran, Renata ; Martinić, Roko ; Štambuk, Ana ; Karaman, Ksenija ; Gagro, Alenka ; Rudolf, Maja ; Malenica, Branko ; Pokrić, Biserka
engleski
Machine learning approach defines immune response during met-enkephalin immunotherapy in multiple sclerosis and optic neuritis.
Peptide therapy has been successfully applied as useful procedure for the treatment of several immune-mediated diseases. Standatd statistical approach based on the comparison of individual parameters is not always appropriate tool for the determination of prognostic parameters defining the response to peptide application. We used another data analysis based on the non-linear machine learning approach with C4.5 decision tree as a classifier. The method has been tested on the model of met-enkephalin, i.e., peptid-M, (LUPEX) vaccination in multiple sclerosis and optic neuritis.
multiple sclerosis; optic neuritis; peptid-M; LUPEX; met-enkephalin; C4.5 classifier; decision making; CD23; CD4; CD8; interferon; LPO; therapy; EDSS; cells
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
Podaci o prilogu
302-305-x.
1998.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the International Conference on Advances in Systems, Signals, Control, Computers : SSCC '98
Bajić, V.B.
Durban: IAAMSAD ; South African branch of the Academy of Nonlinear Sciences
0-620-23135-1
Podaci o skupu
International Conference on Advances in Systems, Signals, Control, Computers : SSCC '98
poster
22.09.1998-24.09.1998
Durban, Južnoafrička Republika
