TransferGWAS on Brain Magnetic Resonance Imaging data: TransferGWAS is an approach to perform genome-wide association studies directly on full medical images. We apply the method on T1-weighted scans of human brains from the UK Biobank dataset. Research conducted together with Remo Monti and Matthias Kirchler.
Syreal (link): Imbalanced training data introduce important challenge into medical image analysis where a majority of the data belongs to a normal class and only few samples belong to abnormal classes. We propose to mitigate the class imbalance problem by introducing two generative adversarial network (GAN) architectures for class minority oversampling.
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