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Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging.

, , , , , , , , , , , and . MLMI@MICCAI, volume 10541 of Lecture Notes in Computer Science, page 371-378. Springer, (2017)

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Editorial: Collaborative Efforts for Understanding the Human Brain., , and . Frontiers Neuroinformatics, (2019)Functional connectivity analysis of resting-state fMRI networks in nicotine dependent patients., , , , , , , and . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 9788 of SPIE Proceedings, page 978827. SPIE, (2016)Deep Learning for Quality Control of Subcortical Brain 3D Shape Models., , , , , , , , , and 3 other author(s). ShapeMI@MICCAI, volume 11167 of Lecture Notes in Computer Science, page 268-276. Springer, (2018)Classification of Major Depressive Disorder via Multi-site Weighted LASSO Model., , , , , , , , , and 6 other author(s). MICCAI (3), volume 10435 of Lecture Notes in Computer Science, page 159-167. Springer, (2017)An evolutionary approach for fMRI big data classification., , , , , , and . CEC, page 1029-1036. IEEE, (2017)Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging., , , , , , , , , and 2 other author(s). MLMI@MICCAI, volume 10541 of Lecture Notes in Computer Science, page 371-378. Springer, (2017)DenseNet and Support Vector Machine classifications of major depressive disorder using vertex-wise cortical features., , , , , , , , , and 78 other author(s). CoRR, (2023)