Advertisement

MODELING FUNCTIONAL CONNECTIVITY CHANGES IN LATE ONSET ALZHEIMER'S DISEASE USING DEEP LEARNING

      Alzheimer’s disease (AD) is known to disrupt resting state functional connectivity (rs-fc) in various brain networks. Predicting functional changes could allow for targeted treatment and improved clinical outcomes for individuals with late onset Alzheimer's disease (LOAD). We propose an ensemble deep learning approach to predict rs-fc changes that occur due to AD.
      To read this article in full you will need to make a payment
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'