Applying machine learning techniques on the diagnosis of Alzheimer disease

 
   Lead Investigator:    Raquel Cacho Zurrunero
   Institution      :    Aalborg University
   E-Mail           :    rcacho18@student.aau.dk
   Proposal ID      :    1215



   Proposal Description:
   The goal is to apply different machine learning techniques to the NACC database in order to build a model which helps in the diagnosis of the Alzheimer disease.         As variables of interest, I would like to focus the project on the analysis of the clinical variables, not the laboratory ones. These variables are those which can be obtained directly by the doctor in the consultant (without external test as image scan or CSF analysis) as age, medical history, health habits or any relevant risk factor. The MMSE examination or similar cognitive test results will be below my interest too.  Finally, I will need a target variable to train my model, and to know how good is his performance. Thus, I will need a variable which indicates the result of the diagnosis by the doctor. In the same path, I have seen that there is also another variable which indicates the presence or not of the disease at the moment of the death, but I don?t know if you have this information for each of the entries (patients) on the general database or instead it is limited to less patients.