Early detection of Alzheimer's using machine learning

 
   Lead Investigator:    Nagarathna C R
   Institution      :    Dsatm
   E-Mail           :    Nagarathna.binu@gmail.com
   Proposal ID      :    1260



   Proposal Description:
   In order to slow down the progression, early diagnosis of the Alzheimer?s disease is important. Also, having an early diagnosis helps people with Alzheimer?s and their families in different ways such a planning for the future, to be concerned on financial and legal matters and making living arrangements. A combination of different modalities like EEG, MRI, PET etc. can help to improve the diagnosis accuracy rate. Research is needed on the combination of modalities to discover multi-modal bio-markers. In our research we will be working on multi-modality like EEG, MRI and PET for early diagnosis of AD. So NACC may help me towards ts direction.    I have plan to implement the project by using Artificial intelligence techniques and I will take care of missing data and so an. Instead of using single modality multi-modality (MRI ,PET SAN EEG) will be used to diagnose AD. Because the combined modalities provide more promising results compared with a single modality. Gathering data set of multi modalities suitable for diagnosis.  Deep machine learning algorithms will be used to learn the generic features from the multimodality brain images. Since the volume of the data will be huge and computationally heavy to handle, artificial intelligence and advanced machine learning techniques will be used for automatic diagnosis of AD. To develop a complete diagnostic system capable of diagnosis early stage Alzheimer?s disease.