A Deep Generative Model Approach To The Genetic Analysis Of Medical Images

I will introduce a new deep generative model for the genetic analysis of medical images, which combines convolutional neural networks and structured linear mixed models [1] to extract latent imaging features in the context of genetic association studies. I will present an application of the method to brain MRI images from the Alzheimer's Disease Neuroimaging Initiative dataset, where we reveal novel and known risk genes for neurological and psychiatric disorders.

Francesco Paolo Casale, Data Scientist at Insitro

I will introduce a new deep generative model for the genetic analysis of medical images, which combines convolutional neural networks and structured linear mixed models [1] to extract latent imaging features in the context of genetic association studies. I will present an application of the method to brain MRI images from the Alzheimer's Disease Neuroimaging Initiative dataset, where we reveal novel and known risk genes for neurological and psychiatric disorders.

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