Using Machine Learning to Forecast the Progression of Alzheimer's Disease

 
   Lead Investigator:    Jack Albright
   Institution      :    The Nueva School
   E-Mail           :    jacalbr@nuevaschool.org
   Proposal ID      :    1183



   Proposal Description:
   Due to the high failure rate among AD drug trials, AD research would benefit from the ability to use patients' biomarkers to predict their mental state in future years, as it would identify patients who are good candidates for           clinical trials before they become symptomatic. Using another source of AD        patient data, I developed a neural network model that was effective at            predicting the progression of AD on a month-by-month basis, both in patients      who were initially cognitively normal and in patients suffering from mild         cognitive impairment. I plan to use the NACC data set to further develop this model as a predictive tool.