Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity

[1]  Juhan Nam,et al.  Multimodal Deep Learning , 2011, ICML.

[2]  Russell A. Poldrack,et al.  Large-scale automated synthesis of human functional neuroimaging data , 2011, Nature Methods.

[3]  Yoshua Bengio,et al.  Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.

[4]  S. Petersen,et al.  The maturing architecture of the brain's default network , 2008, Proceedings of the National Academy of Sciences.

[5]  Naomi B. Pitskel,et al.  Neural signatures of autism , 2010, Proceedings of the National Academy of Sciences.

[6]  Ben Glocker,et al.  Spectral Graph Convolutions for Population-based Disease Prediction , 2017, MICCAI.

[7]  Nicha C. Dvornek,et al.  Learning Generalizable Recurrent Neural Networks from Small Task-fMRI Datasets , 2018, MICCAI.

[8]  Fei-Fei Li,et al.  Deep visual-semantic alignments for generating image descriptions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[9]  Dimitris Samaras,et al.  Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example , 2016, NeuroImage.

[10]  A. Franco,et al.  Identification of autism spectrum disorder using deep learning and the ABIDE dataset , 2017, NeuroImage: Clinical.

[11]  Lukasz Kaiser,et al.  Attention is All you Need , 2017, NIPS.

[12]  Nicha C. Dvornek,et al.  Combining phenotypic and resting-state fMRI data for autism classification with recurrent neural networks , 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

[13]  Khundrakpam Budhachandra,et al.  The Neuro Bureau Preprocessing Initiative: open sharing of preprocessed neuroimaging data and derivatives , 2013 .

[14]  Daniel P. Kennedy,et al.  The Autism Brain Imaging Data Exchange: Towards Large-Scale Evaluation of the Intrinsic Brain Architecture in Autism , 2013, Molecular Psychiatry.

[15]  Nicha C. Dvornek,et al.  Identifying Autism from Resting-State fMRI Using Long Short-Term Memory Networks , 2017, MLMI@MICCAI.