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Studies and
publications

Published Peer-reviewed research has validated the significance of BeCareLink’s data and the correlation with what is clinical standard-of-care.

  • Johnson, L., Fry, A., Dehbandi, B., Rubin, L. G., Halem, M., Barachant, A., Smeragliuolo, A. H., & Putrino, D. (2019). An Automated, Electronic Assessment Tool can Accurately Classify Older Adult Postural Stability. Journal of Biomechanics, 93, 6–10.
  • Litchman, C., Rubin, N., Rubin, L., Litchman, T., Wesely, S., Keaney, J., Vartanian, T., & Stoll, S. (2023). AI Classification of MS disability with the Utilitzation of a Mobile Application. ACTA Scientific Neurology, 6(12). doi: 10.31080/ASNE.2023.06.0688.
  • Litchman, C., Vartanian, T., Rubin, L., Rubin, N., & Stoll, S. (2020). Automated EDSS scoring using a mobile App & Machine Learning. Neurology, 94 (15 Supplement) 2631.
  • Rubin, L., Kruse-Hoyer, M., Litchman, C., Stoll, S,. Putrino, D,. Shetty, S., Engel, C., Marcille, M., Gauthier, S., Perumal, J., Nealon, M., Kaunzer, U., & Vartanian T. (2019). Patient Centered Outcomes Analysis for Multiple Sclerosis Using a Mobile Application. Fourth Annual American Committee for Treatment and Research in Multiple Sclerosis (ACTRIMS).
  • Stoll, S., Litchman, T., Wesley, S., & Litchman, C. (2019) Multiple Sclerosis Apps: The dawn of a new era: A comprehensive review. Neurology, 92 (15 Supplement) P3.2-021.
  • Stoll, S., Rubin, N., Rubin, L., Litchman, T., Keaney, J., Vartanian, T., & C Litchman (2021). Machine Learning Evaluation of MS Patients During the Time of COVID. Neurology, 96 (15 Supplement) 4749.
  • Stoll, S., Litchman, C., Rubin, N., Rubin, L., & Vartanian, T. (2023). Validated, Quantitative, Machine Learning-Generated Neurologic Assessment of Multiple Sclerosis Using a Mobile Application. Int J MS Care.