Publications

2023

  1. Deep multimodal predictome for studying mental disorders
    Md Abdur Rahaman, Jiayu Chen, Zening Fu, and 4 more authors
    Human Brain Mapping, 2023
  2. Deep Generative Transfer Learning Predicts Conversion To Alzheimer’S Disease From Neuroimaging Genomics Data
    G Dolci, MA Rahaman, I Boscolo Galazzo, and 7 more authors
    In 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW), 2023
  3. Deep Generative Transfer Learning Predicts Conversion To Alzheimer’S Disease From Neuroimaging Genomics Data
    G Dolci, MA Rahaman, I Boscolo Galazzo, and 7 more authors
    In 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW), 2023

2022

  1. Two-Dimensional Attentive Fusion for Multi-Modal Learning of Neuroimaging and Genomics Data
    Md Abdur Rahaman, Yash Garg, Armin Iraj, and 3 more authors
    In 2022 IEEE 32nd International Workshop on Machine Learning for Signal Processing (MLSP), 2022
  2. Statelets: Capturing recurrent transient variations in dynamic functional network connectivity
    Md Abdur Rahaman, Eswar Damaraju, Debbrata K Saha, and 2 more authors
    Human Brain Mapping, 2022
  3. Information Bottleneck for Multi-Task LSTMs
    Bradley Thomas Baker, Noah Lewis, Debratta Saha, and 3 more authors
    In NeurIPS 2022 Workshop on Information-Theoretic Principles in Cognitive Systems, 2022
  4. A deep generative multimodal imaging genomics framework for Alzheimer’s disease prediction
    Giorgio Dolci, Md Abdur Rahaman, Jiayu Chen, and 5 more authors
    In 2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE), 2022
  5. Tri-clustering dynamic functional network connectivity identifies significant schizophrenia effects across multiple states in distinct subgroups of individuals
    Md Abdur Rahaman, Eswar Damaraju, Jessica A Turner, and 6 more authors
    Brain connectivity, 2022
  6. Clinical and cortical similarities identified between bipolar disorder I and schizophrenia: A multivariate approach
    Kelly Rootes-Murdy, Jesse T Edmond, Wenhao Jiang, and 8 more authors
    Frontiers in Human Neuroscience, 2022
  7. Longitudinal Whole-Brain Functional Network Change Patterns Over A Two-Year Period In The ABCD Data
    Rekha Saha, Debbrata K Saha, Md Abdur Rahaman, and 2 more authors
    In 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 2022

2021

  1. Multi-modal deep learning of functional and structural neuroimaging and genomic data to predict mental illness
    Md Abdur Rahaman, Jiayu Chen, Zening Fu, and 3 more authors
    In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021
  2. Statelets: A Novel Multi-Dimensional State-Shape Representation Of Brain Functional Connectivity Dynamics
    Md Abdur Rahaman, Eswar Damaraju, Debbrata Kumar Saha, and 2 more authors
    In 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 2021
  3. Shared sets of correlated polygenic risk scores and voxel-wise grey matter across multiple traits identified via bi-clustering
    Md Abdur Rahaman, Amanda Rodrigue, David Glahn, and 2 more authors
    In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021

2020

  1. NeuroMark: An automated and adaptive ICA based pipeline to identify reproducible fMRI markers of brain disorders
    Yuhui Du, Zening Fu, Jing Sui, and 8 more authors
    NeuroImage: Clinical, 2020

2019

  1. N-BiC: A method for multi-component and symptom biclustering of structural MRI data: Application to schizophrenia
    Md Abdur Rahaman, Jessica A Turner, Cota Navin Gupta, and 8 more authors
    IEEE Transactions on Biomedical Engineering, 2019