Prediction of the information processing speed performance in multiple sclerosis using a machine learning approach in a large multicenter magnetic resonance imaging data set.
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| Title: | Prediction of the information processing speed performance in multiple sclerosis using a machine learning approach in a large multicenter magnetic resonance imaging data set. |
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| Authors: | Marzi C; MS Center and 3T-MRI Research Unit, Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania 'Luigi Vanvitelli', Napoli, Italy.; Department of Electrical, Electronic, and Information Engineering 'Guglielmo Marconi' - DEI, Alma Mater Studiorum - University of Bologna, Bologna, Italy., d'Ambrosio A; MS Center and 3T-MRI Research Unit, Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania 'Luigi Vanvitelli', Napoli, Italy., Diciotti S; Department of Electrical, Electronic, and Information Engineering 'Guglielmo Marconi' - DEI, Alma Mater Studiorum - University of Bologna, Bologna, Italy.; Alma Mater Research Institute for Human-Centered Artificial Intelligence, University of Bologna, Bologna, Italy., Bisecco A; MS Center and 3T-MRI Research Unit, Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania 'Luigi Vanvitelli', Napoli, Italy., Altieri M; MS Center and 3T-MRI Research Unit, Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania 'Luigi Vanvitelli', Napoli, Italy.; Department of Psychology, University of Campania 'Luigi Vanvitelli', Napoli, Italy., Filippi M; Neuroimaging Research Unit, Division of Neuroscience, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy.; Neurology and Neurophysiology Unit, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy., Rocca MA; Neuroimaging Research Unit, Division of Neuroscience, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy.; Neurology and Neurophysiology Unit, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy., Storelli L; Neuroimaging Research Unit, Division of Neuroscience, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy., Pantano P; Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy.; IRCCS Neuromed, Pozzilli, Italy., Tommasin S; Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy., Cortese R; Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy., De Stefano N; Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy., Tedeschi G; MS Center and 3T-MRI Research Unit, Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania 'Luigi Vanvitelli', Napoli, Italy., Gallo A; MS Center and 3T-MRI Research Unit, Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania 'Luigi Vanvitelli', Napoli, Italy. |
| Corporate Authors: | INNI Network |
| Source: | Human brain mapping [Hum Brain Mapp] 2023 Jan; Vol. 44 (1), pp. 186-202. Date of Electronic Publication: 2022 Oct 18. |
| Publication Type: | Multicenter Study; Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Wiley Country of Publication: United States NLM ID: 9419065 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-0193 (Electronic) Linking ISSN: 10659471 NLM ISO Abbreviation: Hum Brain Mapp Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1097-0193 |
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| DOI: | 10.1002/hbm.26106 |
