APA (7th ed.) Citation

A, I., E, B., MF, C., M, T., C, M., S, R., . . . M, P. (2026). Predictors of short-term, relapse-independent progression in multiple sclerosis: A machine learning approach based on clinical data and conventional MRI-derived features. Journal of the neurological sciences, 483, 125846. https://doi.org/10.1016/j.jns.2026.125846

Chicago Style (17th ed.) Citation

A, Ianniello, et al. "Predictors of Short-term, Relapse-independent Progression in Multiple Sclerosis: A Machine Learning Approach Based on Clinical Data and Conventional MRI-derived Features." Journal of the Neurological Sciences 483 (2026): 125846. https://doi.org/10.1016/j.jns.2026.125846.

MLA (9th ed.) Citation

A, Ianniello, et al. "Predictors of Short-term, Relapse-independent Progression in Multiple Sclerosis: A Machine Learning Approach Based on Clinical Data and Conventional MRI-derived Features." Journal of the Neurological Sciences, vol. 483, 2026, p. 125846, https://doi.org/10.1016/j.jns.2026.125846.