Alzheimer early predication using Big Data analysis.

 
   Lead Investigator:    Abdal Alsaedi
   Institution      :    Western Michigan University
   E-Mail           :    abdalrahmanfin.alsaedi@wmich.edu
   Proposal ID      :    792


   Publications:


1  Alsaedi A, Mohammad N, Abdel-Qader I, Fong A
   Extended Cox Proportional Hazard Model to Analyze and Predict Conversion From Mild Cognitive Impairment To Alzheimer's Disease
   2018   Abstract  8th IEEE Annual Computing and Communication Workshop and Conference   131-136   , 

   PUBLISHED





   Proposal Description:
   Analyze data from cognitively normal individuals ( age> 50 yrs) to predict        Alzheimer disease. Hadoop ecosystem, and other relative tools, provides a good    environment to analyze BIG medical data.                                          I am trying to discover the relation between some symptoms that can be            considered as pre-Alzheimer by examining the development of particular            symptoms relative to each other. The data that collected from individuals each    year considered as a BIG DATA that if we use Machine Learning Algorithms (MLA)    we can discover new insights form it, these insight can be used a s a             prediction factors forAlzheimer Disease (AD). MLA will be applied in Big Data     infrastructure ( e.g Hadoop).