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Applying deep convolutional neural networks to medical imaging data

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If you have a question about this talk, please contact Rachel Furner.

Recent years have seen an increase in scientific studies applying machine learning methods to medical image analysis. These algorithms have been used in a wide array of problems, ranging from biomarker identification to classifying brain states. Most recently advanced machine learning algorithms known as deep convolutional neural networks (DCNN) have begun to be applied to various medical imaging studies. In this talk I will provide two applications of DCN Ns to medical imaging. The first project uses graph DCN Ns to classify brain networks during rest versus task state. The second uses DCN Ns to identify abnormalities on mammograms.

This talk is part of the CMIH Hub seminar series series.

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