Interpretable deep learning survival predictions in sporadic Creutzfeldt-Jakob disease.

Journal: Journal of neurology
PMID:

Abstract

BACKGROUND: Sporadic Creutzfeldt-Jakob disease (sCJD) is a rapidly progressive and fatal prion disease with significant public health implications. Survival is heterogenous, posing challenges for prognostication and care planning. We developed a survival model using diagnostic data from comprehensive UK sCJD surveillance.

Authors

  • Johnny Tam
  • John Centola
    The UK National CJD Research and Surveillance Unit, Centre for Clinical Brain Sciences, Chancellor's Building, University of Edinburgh, Edinburgh, EH16 4TG, UK.
  • Hatice Kurucu
    The UK National CJD Research and Surveillance Unit, Centre for Clinical Brain Sciences, Chancellor's Building, University of Edinburgh, Edinburgh, EH16 4TG, UK.
  • Neil Watson
    The UK National CJD Research and Surveillance Unit, Centre for Clinical Brain Sciences, Chancellor's Building, University of Edinburgh, Edinburgh, EH16 4TG, UK.
  • Janet MacKenzie
    The UK National CJD Research and Surveillance Unit, Centre for Clinical Brain Sciences, Chancellor's Building, University of Edinburgh, Edinburgh, EH16 4TG, UK.
  • Alison Green
    The UK National CJD Research and Surveillance Unit, Centre for Clinical Brain Sciences, Chancellor's Building, University of Edinburgh, Edinburgh, EH16 4TG, UK.
  • David Summers
    The UK National CJD Research and Surveillance Unit, Centre for Clinical Brain Sciences, Chancellor's Building, University of Edinburgh, Edinburgh, EH16 4TG, UK.
  • Marcelo Barria
    The UK National CJD Research and Surveillance Unit, Centre for Clinical Brain Sciences, Chancellor's Building, University of Edinburgh, Edinburgh, EH16 4TG, UK.
  • Sohan Seth
    School of Informatics, The University of Edinburgh, Edinburgh, UK.
  • Colin Smith
    Department of Biomedical Engineering, Virginia Tech, Blacksburg, Virginia.
  • Suvankar Pal
    The UK National CJD Research and Surveillance Unit, Centre for Clinical Brain Sciences, Chancellor's Building, University of Edinburgh, Edinburgh, EH16 4TG, UK. suvankar.pal@ed.ac.uk.