Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression (vol 208, 106180, 2021)

Paper Info

Title
Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression (vol 208, 106180, 2021)

Year	DOI	Venue
2022	10.1016/j.cmpb.2021.106479	COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
DocType	Volume	ISSN
Journal	213	0169-2607
Citations	PageRank	References
0	0.34	0
Authors
41

Authors (41 rows)

Cited by (0 rows)

References (0 rows)

Name	Order	Citations	PageRank
Edward De Brouwer	1	1	2.37
Thijs Becker	2	0	0.34
Yves Moreau	3	1202	105.05
Eva Kubala Havrdova	4	0	0.34
Maria Trojano	5	0	0.34
Sara Eichau	6	0	0.34
Serkan Ozakbas	7	0	0.34
Marco Onofrj	8	0	0.68
Pierre Grammond	9	0	0.34
Jens Kuhle	10	0	0.34
Ludwig Kappos	11	33	5.32
Patrizia Sola	12	0	0.34
Elisabetta Cartechini	13	0	0.34
Jeannette Lechner-Scott	14	0	0.34
Raed Alroughani	15	0	0.34
Oliver Gerlach	16	0	0.34
Tomas Kalincik	17	0	0.34
Franco Granella	18	0	0.34
Francois Grand'Maison	19	0	0.34
Roberto Bergamaschi	20	5	1.17
Maria José Sá	21	0	0.34
Bart Van Wijmeersch	22	0	0.34
Aysun Soysal	23	0	0.34
Jose Luis Sanchez-Menoyo	24	0	0.34
Claudio Solaro	25	0	0.34
Cavit Boz	26	0	0.34
Gerardo Iuliano	27	0	0.34
Katherine Buzzard	28	0	0.34
Eduardo Aguera-Morales	29	0	0.34
Murat Terzi	30	0	0.34
Tamara Castillo Trivio	31	0	0.34
Daniele Spitaleri	32	0	0.34
Vincent Van Pesch	33	0	0.34
Vahid Shaygannejad	34	0	0.34
Fraser Moore	35	0	0.34
Celia Oreja-Guevara	36	0	0.34
Davide Maimone	37	0	0.34
Riadh Gouider	38	0	0.34
Tunde Csepany	39	0	0.34
Cristina Ramo-Tello	40	0	0.34
Liesbet Peeters	41	0	0.34