Kiret Dhindsa
Cited by
Cited by
Examining the role of the temporo-parietal network in memory, imagery, and viewpoint transformations
K Dhindsa, V Drobinin, J King, GB Hall, N Burgess, S Becker
Frontiers in Human Neuroscience 8, 709, 2014
Filter-Bank Artifact Rejection: High performance real-time single-channel artifact detection for EEG
K Dhindsa
Biomedical Signal Processing and Control 38, 224-235, 2017
What’s holding up the big data revolution in healthcare?
K Dhindsa, M Bhandari, RR Sonnadara
BMJ 363, 2018
From group-level statistics to single-subject prediction: machine learning detection of concussion in retired athletes
R Boshra, K Dhindsa, O Boursalie, KI Ruiter, R Sonnadara, R Samavi, ...
IEEE Transactions on Neural Systems and Rehabilitation Engineering 27 (7 …, 2019
Performance of case-control rare copy number variation annotation in classification of autism
W Engchuan, K Dhindsa, AC Lionel, SW Scherer, JH Chan, D Merico
BMC medical genomics 8 (1), 1-10, 2015
Individualized pattern recognition for detecting mind wandering from EEG during live lectures
K Dhindsa, A Acai, N Wagner, D Bosynak, S Kelly, M Bhandari, B Petrisor, ...
PloS one 14 (9), e0222276, 2019
Using deep learning algorithms to grade hydronephrosis severity: toward a clinical adjunct
LC Smail, K Dhindsa, LH Braga, S Becker, RR Sonnadara
Frontiers in pediatrics 8, 1, 2020
Capturing the forest but missing the trees: microstates inadequate for characterizing shorter-scale EEG dynamics
SB Shaw, K Dhindsa, JP Reilly, S Becker
Neural computation 31 (11), 2177-2211, 2019
Grading Prenatal Hydronephrosis from Ultrasound Imaging using Deep Convolutional Neural Networks
K Dhindsa, LC Smail, M McGrath, LH Braga, S Becker, RR Sonnadara
!5th Conference on Computer and Robot Vision, 80-87, 2018
Toward an open-ended BCI: a user-centered coadaptive design
K Dhindsa, D Carcone, S Becker
Neural computation 29 (10), 2742-2768, 2017
On the time-course of functional connectivity: theory of a dynamic progression of concussion effects
R Boshra, KI Ruiter, K Dhindsa, R Sonnadara, JP Reilly, JF Connolly
Brain Communications 2 (2), fcaa063, 2020
Unsupervised medical image segmentation with adversarial networks: From edge diagrams to segmentation maps
U Sivanesan, LH Braga, RR Sonnadara, K Dhindsa
arXiv preprint arXiv:1911.05140, 2019
Progressive thresholding: shaping and specificity in automated neurofeedback training
K Dhindsa, KD Gauder, KA Marszalek, B Terpou, S Becker
IEEE Transactions on Neural Systems and Rehabilitation Engineering 26 (12 …, 2018
A brain-computer interface based on abstract visual and auditory imagery: evidence for an effect of artistic training
K Dhindsa, D Carcone, S Becker
International Conference on Augmented Cognition, 313-332, 2017
Pancreas adenocarcinoma CT texture analysis: comparison of 3D and 2D tumor segmentation techniques
A Kulkarni, I Carrion-Martinez, K Dhindsa, AA Alaref, R Rozenberg, ...
Abdominal Radiology 46 (3), 1027-1033, 2021
Emotional reaction recognition from EEG
K Dhindsa, S Becker
2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI), 1-4, 2017
MRI LI-RADS version 2018: impact of and reduction in ancillary features
CB van der Pol, K Dhindsa, R Shergill, N Zha, M Ferri, YK Kagoma, ...
American Journal of Roentgenology 216 (4), 935-942, 2021
Generalized Methods for User-Centered Brain-Computer Interfacing
J Dhindsa
An open-ended approach to BCI: Embracing individual differences by allowing for user-defined mental commands
K Dhindsa, D Carcone, S Becker
Frontiers in Computational Neuroscience 9, 2015
Multi-scale brain simulation with integrated positron emission tomography yields hidden local field potential activity that augments machine learning classification of …
P Triebkorn, L Stefanovski, K Dhindsa, MA Diaz-Cortes, P Bey, K Bülau, ...
BioRxiv, 2021
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