Alzheimer's disease classification rate enhanced using missing and imbalanced

 
   Lead Investigator:    Yuri Elias Rodrigues
   Institution      :    Federal University of Rio Grande dos Sul
   E-Mail           :    yuri.rodrigues@acad.pucrs.br
   Proposal ID      :    881



   Proposal Description:
   This research aims to study data science and pattern recognition techniques to    improve dataset quality. In order to this, the main topics to be explored are     oversampling and undersampling methods applied to classification and data         imputation techniques owing to avoid loss of patients' data which exited the      trials. The expected result of this research is to create data science            paradigms which would overcome large trials data quality in classification        studies. It would improve diagnosis, helps to indicate the start of early         palliative therapeutics and identify biomarker combinations that perform          maximally given the study design.