Our research in 2016: personal scientific highlights
Read OriginalThe article details a researcher's 2016 scientific highlights, focusing on neuroimaging and machine learning. Key projects include mapping AI convolutional networks to the human visual system, using resting-state brain activity to predict Autism across clinical sites, and developing a 10x faster algorithm for massive matrix factorization to handle large neuroimaging datasets. It also mentions a review on proper cross-validation practices in neuroimaging.
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