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B1699
Title: Deep learning in neuro-imaging genetics Authors:  Wei Pan - University of Minnesota (United States) [presenting]
Abstract: Several convolutional neural networks/deep learning algorithms are first applied to brain MRI data from the ADNI to extract low-to-high level imaging features, which are then used in downstream analyses of a genome-wide association study (GWAS) to detect genetic variants associated with Alzheimers diseases. We discuss both some promising preliminary results and challenges in our application.