Patient-reported outcomes as predictors of disability evolution in Multiple Sclerosis: An interpretable machine learning approach

The model offers robust and interpretable predictions that may support clinical decision-making using routine clinical data.

Authors

Alice Bollini (ORCID: https://orcid.org/0000-0003-4303-4297)
Margherita Monti Bragadin
Matteo Bauckneht (ORCID: https://orcid.org/0000-0002-1937-9116)
A. Tacchino
Jessica Podda (ORCID: https://orcid.org/0000-0002-9327-9148)
Federica Di Antonio
Silvia Morbelli
Ludovico Pedullà
Valeria Prada
Erica Grange
Giampaolo Brichetto

Institutions

Istituto Nazionale di Fisica Nucleare (IT)
Multiple Sclerosis Foundation (US)
Associazione Italiana Sclerosi Multipla (IT)
Ospedale Policlinico San Martino (IT)
University of Turin (IT)
University of Genoa (IT)

Publication Details

Journal: Multiple Sclerosis Journal
Published: 2026-01-30
DOI: https://doi.org/10.1177/13524585251411093
Primary Topic: Multiple Sclerosis Research Studies
Type: article
Field-Weighted Citation Impact: 0.00

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article

Patient-reported outcomes as predictors of disability evolution in Multiple Sclerosis: An interpretable machine learning approach

Alice Bollini, Margherita Monti Bragadin, Matteo Bauckneht, A. Tacchino et al.

Jan 30, 2026

Multiple Sclerosis Journal

Multiple Sclerosis Research Studies

article

Patient-reported outcomes as predictors of disability evolution in Multiple Sclerosis: An interpretable machine learning approach

Alice Bollini, Margherita Monti Bragadin, Matteo Bauckneht, A. Tacchino, Jessica Podda, Federica Di Antonio, Silvia Morbelli, Ludovico Pedullà, Valeria Prada, Erica Grange, Giampaolo Brichetto

January 30, 2026article en

Abstract

The model offers robust and interpretable predictions that may support clinical decision-making using routine clinical data.

Multiple Sclerosis Journal

Istituto Nazionale di Fisica Nucleare (IT), Multiple Sclerosis Foundation (US), Associazione Italiana Sclerosi Multipla (IT), Ospedale Policlinico San Martino (IT), University of Turin (IT), University of Genoa (IT)

Quality Education

Openalex Percentile: Top 73%

Multiple Sclerosis Research Studies

DOI Open Access PDF OpenAlex

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Patient-reported outcomes as predictors of disability evolution in Multiple Sclerosis: An interpretable machine learning approach — Alice Bollini, Margherita Monti Bragadin, et al. · Multiple Sclerosis Journal (2026) | TGRS Research Map | TGRS