What predicts citation counts and translational impact in headache research? A machine learning analysis.

Journal: Cephalalgia : an international journal of headache
PMID: 38690640

Abstract

BACKGROUND: We aimed to develop the first machine learning models to predict citation counts and the translational impact, defined as inclusion in guidelines or policy documents, of headache research, and assess which factors are most predictive.

Authors

  • Antonios Danelakis
    NorHead Norwegian Centre for Headache Research, NTNU Norwegian University of Science and Technology, 7030, Trondheim, Norway.
  • Helge Langseth
    NorHead Norwegian Centre for Headache Research, NTNU Norwegian University of Science and Technology, 7030, Trondheim, Norway.
  • Parashkev Nachev
    Institute of Neurology, University College London, London, WC1N 3BG, UK.
  • Amy Nelson
    High Dimensional Neurology Group, UCL Queen Square Institute of Neurology, University College London, London, UK.
  • Marte-Helene Bjørk
    NorHead Norwegian Centre for Headache Research, Trondheim, Norway.
  • Manjit S Matharu
    NorHead Norwegian Centre for Headache Research, Trondheim, Norway.
  • Erling Tronvik
    NorHead Norwegian Centre for Headache Research, NTNU Norwegian University of Science and Technology, 7030, Trondheim, Norway.
  • Arne May
    Center for Experimental Medicine, Department of Systems Neuroscience, Universitätsklinikum Hamburg-Eppendorf, Germany.
  • Anker Stubberud
    NorHead Norwegian Centre for Headache Research, NTNU Norwegian University of Science and Technology, 7030, Trondheim, Norway.

Keywords

External Resources

Popular Topics
Recent Journals