Confounder-adjusted MRI-based predictors of multiple sclerosis disability.

Kim, Yujin; Varosanec, Mihael; Kosa, Peter; Bielekova, Bibiana

Kim, Yujin; Varosanec, Mihael; Kosa, Peter; Bielekova, Bibiana.

Afiliación

Kim Y; Laboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, National Institutes of Health, National Institute of Allergy and Infectious Diseases, Bethesda, MD, United States.
Varosanec M; Laboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, National Institutes of Health, National Institute of Allergy and Infectious Diseases, Bethesda, MD, United States.
Kosa P; Laboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, National Institutes of Health, National Institute of Allergy and Infectious Diseases, Bethesda, MD, United States.
Bielekova B; Laboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, National Institutes of Health, National Institute of Allergy and Infectious Diseases, Bethesda, MD, United States.

Front Radiol ; 2: 971157, 2022.

Article en En | MEDLINE | ID: mdl-37492673

Palabras clave

disability outcomes; gradient boosting machine; machine learning; magnetic resonance imaging; multiple sclerosis; physiological confounders

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Radiol Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

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