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Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning
Machine learning has been increasingly used to obtain individualized neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in neuropsychiatric and neurodegenerative disorders.
Applications of Generative Adversarial Networks in Neuroimaging and Clinical Neuroscience
Generative adversarial networks (GANs) are one powerful type of deep learning models that have been successfully utilized in numerous fields.
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