Artificial intelligence extension of the OSCAR-IB criteria

Autor: Petzold, A., Albrecht, P., Balcer, L., Bekkers, E., Brandt, A. U., Calabresi, P. A., Deborah, O. G., Graves, J. S., Green, A., Keane, P. A., Nij Bijvank, J. A., Sander, J. W., Paul, F., Saidha, S., Villoslada, P., Wagner, S. K., Yeh, E. A., Aktas, O., Antel, J., Asgari, N., Audo, I., Avasarala, J., Avril, D., Bagnato, F. R., Banwell, B., Bar-Or, A., Behbehani, R., Manterola, A. B., Bennett, J., Benson, L., Bernard, J., Bremond-Gignac, D., Britze, J., Burton, J., Calkwood, J., Carroll, W., Chandratheva, A., Cohen, J., Comi, G., Cordano, C., Costa, S., Costello, F., Courtney, A., Cruz-Herranz, A., Cutter, G., Crabb, D., Delott, L., De Seze, J., Diem, R., Dollfuss, H., El Ayoubi, N. K., Fasser, C., Finke, C., Fischer, D., Fitzgerald, K., Fonseca, P., Frederiksen, J. L., Frohman, E., Frohman, T., Fujihara, K., Cuellar, I. G., Galetta, S., Garcia-Martin, E., Giovannoni, G., Glebauskiene, B., Suarez, I. G., Jensen, G. P., Hamann, S., Hartung, H. -P., Havla, J., Hemmer, B., Huang, S. -C., Imitola, J., Jasinskas, V., Jiang, H., Kafieh, R., Kappos, L., Kardon, R., Keegan, D., Kildebeck, E., Kim, U. S., Klistorner, S., Knier, B., Kolbe, S., Korn, T., Krupp, L., Lagreze, W., Leocani, L., Levin, N., Liskova, P., Preiningerova, J. L., Lorenz, B., May, E., Miller, D., Mikolajczak, J., Said, S. M., Montalban, X., Morrow, M., Mowry, E., Murta, J., Navas, C., Nolan, R., Nowomiejska, K., Oertel, F. C., Oh, J., Oreja-Guevara, C., Orssaud, C., Osborne, B., Outteryck, O., Paiva, C., Palace, J., Papadopoulou, A., Patsopoulos, N., Pontikos, N., Preising, M., Prince, J., Reich, D., Rejdak, R., Ringelstein, M., Rodriguez de Antonio, L., Sahel, J. -A., Sanchez-Dalmau, B., Sastre-Garriga, J., Schippling, S., Schuman, J., Shindler, K., Shin, R., Shuey, N., Soelberg, K., Specovius, S., Suppiej, A., Thompson, A., Toosy, A., Torres, R., Touitou, V., Trauzettel-Klosinski, S., van der Walt, A., Vermersch, P., Vidal-Jordana, A., Waldman, A. T., Waters, C., Wheeler, R., White, O., Wilhelm, H., Winges, K. M., Wiegerinck, N., Wiehe, L., Wisnewski, T., Wong, S., Wurfel, J., Yaghi, S., You, Y., Yu, Z., Yu-Wai-Man, P., Zemaitien≐, R., Zimmermann, H.

Publikováno v: Petzold, A, Albrecht, P, Balcer, L, Bekkers, E, Brandt, A U, Calabresi, P A, Deborah, O G, Graves, J S, Green, A, Keane, P A, Nij Bijvank, J A, Sander, J W, Paul, F, Saidha, S, Villoslada, P, Wagner, S K, Yeh, E A & the IMSVISUAL, ERN-EYE Consortium 2021, ' Artificial intelligence extension of the OSCAR-IB criteria ', Annals of Clinical and Translational Neurology, vol. 8, no. 7, pp. 1528-1542 . https://doi.org/10.1002/acn3.51320
the IMSVISUAL, ERN-EYE Consortium 2021, ' Artificial intelligence extension of the OSCAR-IB criteria ', Annals of Clinical and Translational Neurology, vol. 8, no. 7, pp. 1528-1542 . https://doi.org/10.1002/acn3.51320
Annals of Clinical and Translational Neurology
Annals of Clinical and Translational Neurology, Vol 8, Iss 7, Pp 1528-1542 (2021)

Artificial intelligence (AI)‐based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big dat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab75a15c7ed188859f7ddc8d47650216
https://openaccess.city.ac.uk/id/eprint/26361/1/acn3.51320.pdf

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Association of genetic markers with CSF oligoclonal bands in multiple sclerosis patients

Autor: Leone, M, Barizzone, N, Esposito, F, Harbo, H, Goris, A, Kockum, I, Oturai, A, Celius, E, Mero, I, Dubois, B, Olsson, T, Søndergaard, H, Cusi, D, Lupoli, S, Andreassen, B, Barcellos, L, Booth, D, Comabella, M, Compston, A, D'Alfonso, S, De Jager, P, Fontaine, B, Hafler, D, Haines, J, Hauser, S, Hawkins, C, Hemmer, B, Hillert, J, Ivinson, A, Martin, R, Martinelli Boneschi, F, Mccauley, J, Oksenberg, J, Patsopoulos, N, Pericak Vance, M, Saarela, J, Sawcer, S, Spurkland, A, Stewart, G, Zipp, F, Myhr, K, Guerini, F, Naldi, P, Galimberti, D, Scarpini, E, Bergamaschi, R, Di Sapio, A, Caputo, D, Rosso, G, Cordera, S, Cavalla, P, Cavallo, R, Benedetti, M, Salvetti, M, Capra, R, Ghezzi, A, Annovazzi, P, Coniglio, G, Liberatore, G, Rodegher, M, Moiola, L, Colombo, B, Radaelli, M, Rossi, P, Martinelli, V, Comi, G, D'Alfonso, S., LUCENTI, AUSILIATRICE

Publikováno v: PLoS ONE, Vol 8, Iss 6, p e64408 (2013)
Leone, MA; Barizzone, N; Esposito, F; Lucenti, A; Harbo, HF; Goris, A; et al.(2013). Association of Genetic Markers with CSF Oligoclonal Bands in Multiple Sclerosis Patients. PLoS ONE, 8(6). doi: 10.1371/journal.pone.0064408. UCSF: Retrieved from: http://www.escholarship.org/uc/item/3z49w28d
PloS one, vol 8, iss 6
PLoS ONE

Objective:to explore the association between genetic markers and Oligoclonal Bands (OCB) in the Cerebro Spinal Fluid (CSF) of Italian Multiple Sclerosis patients.Methods:We genotyped 1115 Italian patients for HLA-DRB1*15 and HLA-A*02. In a subset of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d219d00494b46e631a75d4423938f74e
http://europepmc.org/articles/PMC3681825?pdf=render

A gene pathway analysis highlights the role of cellular adhesion molecules in multiple sclerosis susceptibility

Autor: Damotte, V, Guillot-Noel, L, Patsopoulos, N A, Madireddy, L, El Behi, M, De Jager, P L, Baranzini, S E, Cournu-Rebeix, I, Fontaine, B, Martin, R

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1517ee9ae76f56d2d999446cd4b5568
https://doi.org/10.5167/uzh-95750