| M-gcn: A multimodal graph convolutional network to integrate functional and structural connectomics data to predict multidimensional phenotypic characterizations NS Dsouza, MB Nebel, D Crocetti, J Robinson, S Mostofsky, ... Medical Imaging with Deep Learning, 119-130, 2021 | 37 | 2021 |
| Integrating neural networks and dictionary learning for multidimensional clinical characterizations from functional connectomics data NS D’Souza, MB Nebel, N Wymbs, S Mostofsky, A Venkataraman Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 19 | 2019 |
| Deep sr-DDL: Deep structurally regularized dynamic dictionary learning to integrate multimodal and dynamic functional connectomics data for multidimensional clinical … NS D’Souza, MB Nebel, D Crocetti, J Robinson, N Wymbs, SH Mostofsky, ... NeuroImage 241, 118388, 2021 | 12 | 2021 |
| A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes NS D'Souza, MB Nebel, D Crocetti, N Wymbs, J Robinson, S Mostofsky, ... International Conference on Medical Image Computing and Computer Assisted …, 2021 | 12 | 2021 |
| A deep-generative hybrid model to integrate multimodal and dynamic connectivity for predicting spectrum-level deficits in autism NS D’Souza, MB Nebel, D Crocetti, N Wymbs, J Robinson, S Mostofsky, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 12 | 2020 |
| A joint network optimization framework to predict clinical severity from resting state functional MRI data NS D’Souza, MB Nebel, N Wymbs, SH Mostofsky, A Venkataraman NeuroImage 206, 116314, 2020 | 11 | 2020 |
| A generative-discriminative basis learning framework to predict clinical severity from resting state functional MRI data NS D’Souza, MB Nebel, N Wymbs, S Mostofsky, A Venkataraman Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 11 | 2018 |
| A coupled manifold optimization framework to jointly model the functional connectomics and behavioral data spaces NS D’Souza, MB Nebel, N Wymbs, S Mostofsky, A Venkataraman Information Processing in Medical Imaging: 26th International Conference …, 2019 | 8 | 2019 |
| A Multi-Task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients using Both Static and Dynamic Functional Connectivity N Nandakumar, NS D'Souza, K Manzoor, J Pillai, S Gujar, S Agarwal, ... MLCN: MICCAI Workshop on Machine Learning for Clinical Neuroimaging, 2020 | 7* | 2020 |
| Fusing modalities by multiplexed graph neural networks for outcome prediction in tuberculosis NS D’Souza, H Wang, A Giovannini, A Foncubierta-Rodriguez, KL Beck, ... International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 6 | 2022 |
| Medical Imaging with Deep Learning NS Dsouza, MB Nebel, D Crocetti, J Robinson, S Mostofsky, ... PMLR, 2021 | 6 | 2021 |
| Defining patient specific functional parcellations in lesional cohorts via Markov random fields N Nandakumar, NS D’Souza, J Craley, K Manzoor, JJ Pillai, SK Gujar, ... Connectomics in NeuroImaging: Second International Workshop, CNI 2018, Held …, 2018 | 6 | 2018 |
| mSPD-NN: A Geometrically Aware Neural Framework for Biomarker Discovery from Functional Connectomics Manifolds NS D’Souza, A Venkataraman International Conference on Information Processing in Medical Imaging, 53-65, 2023 | 3 | 2023 |
| Predicting acute kidney injury via interpretable ensemble learning and attention weighted convoutional-recurrent neural networks YC Peng, NS D'Souza, B Bush, C Brown, A Venkataraman 2021 55th Annual Conference on Information Sciences and Systems (CISS), 1-6, 2021 | 2 | 2021 |
| Fusing modalities by multiplexed graph neural networks for outcome prediction from medical data and beyond NS D‘Souza, H Wang, A Giovannini, A Foncubierta-Rodriguez, KL Beck, ... Medical Image Analysis 93, 103064, 2024 | 1 | 2024 |
| Feature Selection for Malapposition Detection in Intravascular Ultrasound-A Comparative Study S Kashyap, N Karani, A Shang, N D’Souza, N Dey, L Jain, R Wang, ... International Workshop on Applications of Medical AI, 165-175, 2023 | 1 | 2023 |
| MaxCorrMGNN: A Multi-graph Neural Network Framework for Generalized Multimodal Fusion of Medical Data for Outcome Prediction NS D’Souza, H Wang, A Giovannini, A Foncubierta-Rodriguez, KL Beck, ... Workshop on Machine Learning for Multimodal Healthcare Data, 141-154, 2023 | 1 | 2023 |
| Multiplexed graph neural networks for multimodal fusion N DSouza, T Syeda-Mahmood, A Giovannini, AF Rodriguez US Patent App. 17/933,468, 2024 | | 2024 |
| Multimodal Sleep Apnea Detection with Missing or Noisy Modalities H Fayyaz, A Strang, NS D'Souza, R Beheshti arXiv preprint arXiv:2402.17788, 2024 | | 2024 |
| Multimodal data inference A Giovannini, AF Rodriguez, N DSouza, T Syeda-Mahmood, H Wang US Patent App. 17/806,556, 2023 | | 2023 |
Archana VenkataramanJohns Hopkins UniversityVerified email at jhu.edu
