Predictors of short-term, relapse-independent progression in multiple sclerosis: A machine learning approach based on clinical data and conventional MRI-derived features.

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Title: Predictors of short-term, relapse-independent progression in multiple sclerosis: A machine learning approach based on clinical data and conventional MRI-derived features.
Authors: Ianniello A; Department of Human Neurosciences, Sapienza University of Rome, Italy; Multiple Sclerosis Center, San Pietro Fatebenetratelli, Rome, Italy., Barbuti E; Department of Human Neurosciences, Sapienza University of Rome, Italy., Capobianco MF; Department of Neurosciences and Reproductive and Odontostomatological Sciences, University 'Federico II', 80131 Naples, Italy., Tranfa M; Department of Advanced Biomedical Sciences, University 'Federico II', Naples, Italy; Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands., Miele C; Department of Medicine, Surgery and Dentistry, University of Salerno, Baronissi, Italy., Ruggieri S; Department of Neurosciences, San Camillo-Forlanini Hospital, Rome, Italy., Pontillo G; Department of Advanced Biomedical Sciences, University 'Federico II', Naples, Italy; Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, UK., Cocozza S; Department of Advanced Biomedical Sciences, University 'Federico II', Naples, Italy., Pantano P; Department of Human Neurosciences, Sapienza University of Rome, Italy; IRCCS Neuromed, Pozzilli, IS, Italy., Pozzilli C; Department of Human Neurosciences, Sapienza University of Rome, Italy., Cuocolo R; Department of Medicine, Surgery and Dentistry, University of Salerno, Baronissi, Italy. Electronic address: rcuocolo@unisa.it., Petracca M; Department of Human Neurosciences, Sapienza University of Rome, Italy.
Source: Journal of the neurological sciences [J Neurol Sci] 2026 Apr 15; Vol. 483, pp. 125846. Date of Electronic Publication: 2026 Feb 28.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0375403 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1878-5883 (Electronic) Linking ISSN: 0022510X NLM ISO Abbreviation: J Neurol Sci Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1878-5883
DOI:10.1016/j.jns.2026.125846