Anees Abrol
Anees Abrol
Research Scientist II, GSU/GATech/Emory TReNDS Center
Verified email at - Homepage
Cited by
Cited by
NeuroMark: An automated and adaptive ICA based pipeline to identify reproducible fMRI markers of brain disorders
Y Du, Z Fu, J Sui, S Gao, Y Xing, D Lin, M Salman, A Abrol, MA Rahaman, ...
NeuroImage: Clinical 28, 102375, 2020
Replicability of time-varying connectivity patterns in large resting state fMRI samples
A Abrol, E Damaraju, RL Miller, JM Stephen, ED Claus, AR Mayer, ...
Neuroimage 163, 160-176, 2017
Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning
A Abrol, Z Fu, M Salman, R Silva, Y Du, S Plis, V Calhoun
Nature communications 12 (1), 353, 2021
Deep residual learning for neuroimaging: an application to predict progression to Alzheimer’s disease
A Abrol, M Bhattarai, A Fedorov, Y Du, S Plis, V Calhoun, ...
Journal of neuroscience methods 339, 108701, 2020
A phase II study repurposing atomoxetine for neuroprotection in mild cognitive impairment
AI Levey, D Qiu, L Zhao, WT Hu, DM Duong, L Higginbotham, ...
Brain,, 2021
Multimodal data fusion of deep learning and dynamic functional connectivity features to predict Alzheimer’s disease progression
A Abrol, Z Fu, Y Du, VD Calhoun
2019 41st annual international conference of the IEEE engineering in …, 2019
Determining the number of states in dynamic functional connectivity using cluster validity indexes
VM Vergara, M Salman, A Abrol, FA Espinoza, VD Calhoun
Journal of neuroscience methods 337, 108651, 2020
Age‐related structural and functional variations in 5,967 individuals across the adult lifespan
N Luo, J Sui, A Abrol, D Lin, J Chen, VM Vergara, Z Fu, Y Du, E Damaraju, ...
Human brain mapping 41 (7), 1725-1737, 2020
The chronnectome: Evaluating replicability of dynamic connectivity patterns in 7500 resting fMRI datasets
A Abrol, C Chaze, E Damaraju, VD Calhoun
2016 38th Annual International Conference of the IEEE Engineering in …, 2016
Deep learning in neuroimaging: Promises and challenges
W Yan, G Qu, W Hu, A Abrol, B Cai, C Qiao, SM Plis, YP Wang, J Sui, ...
IEEE Signal Processing Magazine 39 (2), 87-98, 2022
Structural brain architectures match intrinsic functional networks and vary across domains: a study from 15 000+ individuals
N Luo, J Sui, A Abrol, J Chen, JA Turner, E Damaraju, Z Fu, L Fan, D Lin, ...
Cerebral Cortex 30 (10), 5460-5470, 2020
An average sliding window correlation method for dynamic functional connectivity
VM Vergara, A Abrol, VD Calhoun
Human Brain Mapping 40 (7), 2089-2103, 2019
Resting-state fMRI dynamics and null models: perspectives, sampling variability, and simulations
RL Miller, A Abrol, T Adali, Y Levin-Schwarz, VD Calhoun
Frontiers in neuroscience 12, 551, 2018
Schizophrenia shows disrupted links between brain volume and dynamic functional connectivity
A Abrol, B Rashid, S Rachakonda, E Damaraju, VD Calhoun
Frontiers in neuroscience 11, 305413, 2017
Prediction of Progression to Alzheimer's disease with Deep InfoMax
A Fedorov, RD Hjelm, A Abrol, Z Fu, Y Du, S Plis, VD Calhoun
2019 IEEE EMBS International conference on biomedical & health informatics …, 2019
Evidence of shared and distinct functional and structural brain signatures in schizophrenia and autism spectrum disorder
Y Du, Z Fu, Y Xing, D Lin, G Pearlson, P Kochunov, LE Hong, S Qi, ...
Communications biology 4 (1), 1073, 2021
Development of digital voice biomarkers and associations with cognition, cerebrospinal biomarkers, and neural representation in early Alzheimer's disease
I Hajjar, M Okafor, JD Choi, E Moore, A Abrol, VD Calhoun, FC Goldstein
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring 15 (1 …, 2023
A classification-based approach to estimate the number of resting functional magnetic resonance imaging dynamic functional connectivity states
DK Saha, E Damaraju, B Rashid, A Abrol, SM Plis, VD Calhoun
Brain connectivity 11 (2), 132-145, 2021
Addressing inaccurate nosology in mental health: A multilabel data cleansing approach for detecting label noise from structural magnetic resonance imaging data in mood and …
H Rokham, G Pearlson, A Abrol, H Falakshahi, S Plis, VD Calhoun
Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 5 (8), 819-832, 2020
Decentralized temporal independent component analysis: leveraging fMRI data in collaborative settings
BT Baker, A Abrol, RF Silva, E Damaraju, AD Sarwate, VD Calhoun, ...
NeuroImage 186, 557-569, 2019
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