Disentangling brain heterogeneity via semi-supervised deep-learning and MRI: dimensional representations of Alzheimer’s Disease. (arXiv:2102.12582v1 [cs.LG])

Heterogeneity of brain diseases is a challenge for precision diagnosis/prognosis. We describe and validate Smile-GAN (SeMI-supervised cLustEring-Generative Adversarial Network), a novel semi-supervised deep-clustering method, which dissects neuroanatomical heterogeneity, enabling identification

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