出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Since the mid of 1990s, functional connectivity study using fMRI (fcMRI) has drawn increasingattention of neuroscientists and computer scientists, since it opens a new window to explorefunctional network of human brain with relatively high resolution. BOLD technique providesalmost accurate state of brain. Past researches prove that neuro diseases damage the brainnetwork interaction, protein- protein interaction and gene-gene interaction. A number ofneurological research paper also analyse the relationship among damaged part. Bycomputational method especially machine learning technique we can show such classifications.In this paper we used OASIS fMRI dataset affected with Alzheimer’s disease and normalpatient’s dataset. After proper processing the fMRI data we use the processed data to formclassifier models using SVM (Support Vector Machine), KNN (K- nearest neighbour) & NaïveBayes. We also compare the accuracy of our proposed method with existing methods. In future,we will other combinations of methods for better accuracy.
