Anees Abrol

Orcid: 0000-0001-9223-5314

According to our database1, Anees Abrol authored at least 39 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Intra-Atlas Node Size Effects on Graph Metrics in fMRI Data: Implications for Alzheimer's Disease and Cognitive Impairment.
Sensors, February, 2024

Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities.
NeuroImage, 2024

Gray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity.
NeuroImage, 2024

Hierarchical Spatio-Temporal State-Space Modeling for fMRI Analysis.
CoRR, 2024

A deep spatio-temporal attention model of dynamic functional network connectivity shows sensitivity to Alzheimer's in asymptomatic individuals.
CoRR, 2024

Multimodal MRI-based Detection of Amyloid Status in Alzheimer's Disease Continuum.
CoRR, 2024

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease.
CoRR, 2024

Cross-Modality Translation with Generative Adversarial Networks to Unveil Alzheimer's Disease Biomarkers.
CoRR, 2024

Voxelwise Intensity Projection for the Spatial Representation of Resting State Functional MRI Networks and Multimodal Deep Learning.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Cross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs.
Proceedings of the IEEE International Conference on Acoustics, 2024

A Novel Deep Subspace Learning Framework to Automatically Uncover Assessment-Specific Independent Brain Networks.
Proceedings of the 58th Annual Conference on Information Sciences and Systems, 2024

2023
MultiViT: Multimodal Vision Transformer for Schizophrenia Prediction using Structural MRI and Functional Network Connectivity Data.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

A Multimodal Deep Learning Approach for Automated Detection and Characterization of Distinctly Salient Features of Alzheimers Disease.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Deep Generative Transfer Learning Predicts Conversion To Alzheimer'S Disease From Neuroimaging Genomics Data.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
Deep Learning in Neuroimaging: Promises and challenges.
IEEE Signal Process. Mag., 2022

Building Models of Functional Interactions Among Brain Domains that Encode Varying Information Complexity: A Schizophrenia Case Study.
Neuroinformatics, 2022

Pipeline-Invariant Representation Learning for Neuroimaging.
CoRR, 2022

An Approach to Automatically Label and Order Brain Activity/Component Maps.
Brain Connect., 2022

Deep Learning Prediction and Visualization of Gender Related Brain Changes from Longitudinal Structural MRI Data in the ABCD Study.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Learning Active Multimodal Subspaces in the Brain.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Probing the link between the APOE-ε4 allele and whole-brain gray matter using deep learning.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Discovery and Replication of Time-Resolved Functional Network Connectivity Differences in Adolescence and Adulthood in over 50K fMRI Datasets.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

A deep generative multimodal imaging genomics framework for Alzheimer's disease prediction.
Proceedings of the 22nd IEEE International Conference on Bioinformatics and Bioengineering, 2022

Classification of Schizophrenia and Alzheimer's Disease using Resting-State Functional Network Connectivity.
Proceedings of the IEEE-EMBS International Conference on Biomedical and Health Informatics, 2022

2021
A Classification-Based Approach to Estimate the Number of Resting Functional Magnetic Resonance Imaging Dynamic Functional Connectivity States.
Brain Connect., 2021

A Multimodal Learning Framework to Study Varying Information Complexity in Structural and Functional Sub-Domains in Schizophrenia.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Uncovering Active Structural Subspaces Associated with Changes in Indicators for Alzheimer's Disease.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Deep learning in resting-state fMRI<sup>*</sup>.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

2020
Functional Multi-Connectivity: A Novel Approach To Assess Multi-Way Entanglement Between Networks and Voxels.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Fully automated ordering and labeling of ICA components.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

Varying Information Complexity in Functional Domain Interactions in Schizophrenia.
Proceedings of the 20th IEEE International Conference on Bioinformatics and Bioengineering, 2020

2019
Decentralized temporal independent component analysis: Leveraging fMRI data in collaborative settings.
NeuroImage, 2019

Classification As a Criterion to Select Model Order For Dynamic Functional Connectivity States in Rest-fMRI Data.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Selection of Efficient Clustering Index to Estimate the Number of Dynamic Brain States from Functional Network Connectivity.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

Diagnostic and Prognostic Classification of Brain Disorders Using Residual Learning on Structural MRI Data.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

Multimodal Data Fusion of Deep Learning and Dynamic Functional Connectivity Features to Predict Alzheimer's Disease Progression.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

Prediction of Progression to Alzheimer's disease with Deep InfoMax.
Proceedings of the 2019 IEEE EMBS International Conference on Biomedical & Health Informatics, 2019

2017
Replicability of time-varying connectivity patterns in large resting state fMRI samples.
NeuroImage, 2017

2016
The chronnectome: Evaluating replicability of dynamic connectivity patterns in 7500 resting fMRI datasets.
Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016


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