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Index by author

November 01, 2021; Volume 42,Issue 11

  1. Tedeschi, E.

    1. EDITOR'S CHOICEAdult Brain
      Open Access
      A Combined Radiomics and Machine Learning Approach to Overcome the Clinicoradiologic Paradox in Multiple Sclerosis
      G. Pontillo, S. Tommasin, R. Cuocolo, M. Petracca, N. Petsas, L. Ugga, A. Carotenuto, C. Pozzilli, R. Iodice, R. Lanzillo, M. Quarantelli, V. Brescia Morra, E. Tedeschi, P. Pantano and S. Cocozza
      American Journal of Neuroradiology November 2021, 42 (11) 1927-1933; DOI: https://doi.org/10.3174/ajnr.A7274

      The multidimensional analysis of brain MR images, including radiomic features and clinicodemographic data, is highly informative of the clinical status of patients with multiple sclerosis, representing a promising approach to bridge the gap between conventional imaging and disability.

  2. Thomas, Bejoy

    1. Perspectives
      Bejoy Thomas
      American Journal of Neuroradiology November 2021, 42 (11) 1919; DOI: https://doi.org/10.3174/ajnr.P0116

  3. Tommasin, S.

    1. EDITOR'S CHOICEAdult Brain
      Open Access
      A Combined Radiomics and Machine Learning Approach to Overcome the Clinicoradiologic Paradox in Multiple Sclerosis
      G. Pontillo, S. Tommasin, R. Cuocolo, M. Petracca, N. Petsas, L. Ugga, A. Carotenuto, C. Pozzilli, R. Iodice, R. Lanzillo, M. Quarantelli, V. Brescia Morra, E. Tedeschi, P. Pantano and S. Cocozza
      American Journal of Neuroradiology November 2021, 42 (11) 1927-1933; DOI: https://doi.org/10.3174/ajnr.A7274

      The multidimensional analysis of brain MR images, including radiomic features and clinicodemographic data, is highly informative of the clinical status of patients with multiple sclerosis, representing a promising approach to bridge the gap between conventional imaging and disability.

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