Developing and validating a prediction tool for cerebral amyloid angiopathy neuropathological severity.

Journal: Alzheimer's & dementia : the journal of the Alzheimer's Association
PMID: 40042448

Abstract

INTRODUCTION: Cerebral amyloid angiopathy (CAA) is a cerebrovascular condition, the severity of which can only be determined post mortem. Here, we developed machine learning models, the Florey CAA Score (FCAAS), to predict CAA severity (none/mild/moderate/severe).

Authors

  • Chenyin Chu
    The Florey Institute of Neuroscience and Mental Health, 30 Royal Parade, Parkville, VIC, 3052, Australia.
  • Yihan Wang
    Vanderbilt University Medical Center, Nashville TN 37232, USA.
  • Liwei Ma
    The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia.
  • Chloe A Mutimer
    Department of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia.
  • Guangyan Ji
    The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia.
  • Huiyu Shi
    The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia.
  • Nawaf Yassi
  • Colin L Masters
    Florey Institute, The University of Melbourne, Parkville, VIC, 3052, Australia.
  • Benjamin Goudey
    Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.
  • Liang Jin
    Radiology Department, Huadong Hospital, Affiliated with Fudan University, Shanghai, China.
  • Yijun Pan
    The Florey Institute of Neuroscience and Mental Health, 30 Royal Parade, Parkville, VIC, 3052, Australia. yijun.pan@unimelb.edu.au.

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