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Investigator's Name: Onur Erdoğan
Proposed Analysis: Main goal of my research towards my doctoral degree, is to develop a predictive AD model with the highest classification performance. We will perform the meta-analysis of different AD data sets (ADNI, dbGAP, in-house…) separately, which have been obtained independently so far, and apply different types of hybrid data mining approaches for both the preprocessing step and the model construction. After statistical meta-analysis of each dataset, Analytical Hierarchy Process (AHP) or Random Forest (RF) technique will be implemented. Different combinations among the avaiable data-mining approaches will be used to determine the hybrid decision model with performance. Belief networks methods and other emerging apporaches will Be utilized for finalizing the meta-model, based on the large scale genotype-phenotype association data. Uncovering the genetic basis for disease is the critical step toward the goal of developing an effective system of “personalized” medicine.