Using multivariate machine-learning tools to aid early and accurate diagnosis
of dementia and risk factor identification.
 
   Lead Investigator:    Anna Zvikhachevskaya
   Institution      :    IXICO PLC
   E-Mail           :    anna.zvikhachevskaya@ixico.com
   Proposal ID      :    556



   Proposal Description:
   Research Question 1: Predicting dementia progression while focusing on the behavior characteristics, cognitive functions, therapies, motor symptoms, and overall clinical summary of symptom offset.                                       Methodology 1: Statistical methods for tracking the clinical course will include sample size estimation, classifications, machine learning, assessment of the predictive factors, clinical progression and patterns, medications and therapies prescribed that may potentially impact the course of progression of cognition, function, behavior, quality of life, and clinical milestones in healthy cognitive aging, cognitive impairment, and dementia, including the Alzheimer???s disease spectrum.                                                   Development Aim 1: To develop and provide advanced tools and programs, to assist researchers to understand data, better classify and track performance on clinical tests and measures, predict progression.                                                                                                                   Research Question 2: We also aim to assess the impact of White Matter Hyperintesity (WMH), atrophy patterns and cognition. We intent to assess on subjects for which an MRI is available (No MRI shouldn???t be an exclusion criteria), whether there???s any association between cognition at the time of diagnosis visit and degree of the condition and location of hyperintensities.     Is there a relationship between WMH and change in brain or hippocampal volume using serial T1 weighted imaging?                                                 Development Aim 2: To predict the cognitive decline based on WMH and atrophy patterns and link it to the Research questions 1.                                 Resulting outcome:                                                                ???Developed predictive model that will aim to help understanding of weighting scheme between risk factors and progression pre