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Scientific Reports|August 1, 2020
Inferring disease subtypes from clusters in explanation spaceMarc-Andre Schulz, Matt Chapman-Rounds, Manisha Verma, et al.Cell Reports|December 30, 2023
Performance reserves in brain-imaging-based phenotype predictionMarc-Andre Schulz, Danilo Bzdok, Stefan Haufe, et al.Frontiers in Neuroscience|October 24, 2017
Classical Statistics and Statistical Learning in Imaging NeuroscienceDanilo BzdokNature Communications|August 27, 2020
Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasetsMarc-Andre Schulz, B T Thomas Yeo, Joshua T Vogelstein, et al.The Behavioral and Brain Sciences|November 11, 2017
Contempt - Where the modularity of the mind meets the modularity of the brain?Danilo Bzdok, Leonhard SchilbachNeural Networks : the Official Journal of the International Neural Network Society|July 1, 2022
From YouTube to the brain: Transfer learning can improve brain-imaging predictions with deep learningNahiyan Malik, Danilo BzdokMolecular Psychiatry|May 2, 2020
Autism spectrum heterogeneity: fact or artifact?Laurent Mottron, Danilo BzdokAdvances in Geriatric Medicine and Research|April 21, 2021
Loneliness and Neurocognitive AgingR Nathan Spreng, Danilo BzdokBiological Psychiatry. Cognitive Neuroscience and Neuroimaging|March 1, 2018
Machine Learning for Precision Psychiatry: Opportunities and ChallengesDanilo Bzdok, Andreas Meyer-LindenbergPageof 29