Niharika Shimona D'Souza
According to our database1,
Niharika Shimona D'Souza
authored at least 21 papers
between 2018 and 2024.
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Bibliography
2024
Fusing modalities by multiplexed graph neural networks for outcome prediction from medical data and beyond.
Medical Image Anal., 2024
Modern Hopfield Networks meet Encoded Neural Representations - Addressing Practical Considerations.
CoRR, 2024
Geo-UNet: A Geometrically Constrained Neural Framework for Clinical-Grade Lumen Segmentation in Intravascular Ultrasound.
Proceedings of the Machine Learning in Medical Imaging - 15th International Workshop, 2024
2023
MaxCorrMGNN: A Multi-graph Neural Network Framework for Generalized Multimodal Fusion of Medical Data for Outcome Prediction.
Proceedings of the Machine Learning for Multimodal Healthcare Data, 2023
Feature Selection for Malapposition Detection in Intravascular Ultrasound - A Comparative Study.
Proceedings of the Applications of Medical Artificial Intelligence, 2023
mSPD-NN: A Geometrically Aware Neural Framework for Biomarker Discovery from Functional Connectomics Manifolds.
Proceedings of the Information Processing in Medical Imaging, 2023
2022
Fusing Modalities by Multiplexed Graph Neural Networks for Outcome Prediction in Tuberculosis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
2021
Deep sr-DDL: Deep structurally regularized dynamic dictionary learning to integrate multimodal and dynamic functional connectomics data for multidimensional clinical characterizations.
NeuroImage, 2021
A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes.
CoRR, 2021
M-GCN: A Multimodal Graph Convolutional Network to Integrate Functional and Structural Connectomics Data to Predict Multidimensional Phenotypic Characterizations.
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021
A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Predicting Acute Kidney Injury via Interpretable Ensemble Learning and Attention Weighted Convoutional-Recurrent Neural Networks.
Proceedings of the 55th Annual Conference on Information Sciences and Systems, 2021
2020
A joint network optimization framework to predict clinical severity from resting state functional MRI data.
NeuroImage, 2020
A Multi-task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients Using Dynamic Functional Connectivity.
Proceedings of the Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology, 2020
A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
2019
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces.
Proceedings of the Information Processing in Medical Imaging, 2019
2018
Defining Patient Specific Functional Parcellations in Lesional Cohorts via Markov Random Fields.
Proceedings of the Connectomics in NeuroImaging - Second International Workshop, 2018
A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018