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Outliers in neuroimaging represent spurious data or the data of unusual phenotypes that deserve special attention such as clinical follow‐up. Outliers have usually been detected in a supervised or semi‐supervised manner for labeled neuroimaging cohorts. There has been much less work using unsupervised outlier detection on large unlabeled cohorts like the UK Biobank brain imaging dataset. Given its...
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