Bryan Conroy
Bryan Conroy
Senior Scientist, Philips Research North America
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Cited by
Cited by
A common, high-dimensional model of the representational space in human ventral temporal cortex
JV Haxby, JS Guntupalli, AC Connolly, YO Halchenko, BR Conroy, ...
Neuron 72 (2), 404-416, 2011
Ensemble of feature-based and deep learning-based classifiers for detection of abnormal heart sounds
C Potes, S Parvaneh, A Rahman, B Conroy
2016 computing in cardiology conference (CinC), 621-624, 2016
Function-based intersubject alignment of human cortical anatomy
MR Sabuncu, BD Singer, B Conroy, RE Bryan, PJ Ramadge, JV Haxby
Cerebral cortex 20 (1), 130-140, 2010
Inter-subject alignment of human cortical anatomy using functional connectivity
BR Conroy, BD Singer, JS Guntupalli, PJ Ramadge, JV Haxby
NeuroImage 81, 400-411, 2013
Densely connected convolutional networks for detection of atrial fibrillation from short single-lead ECG recordings
J Rubin, S Parvaneh, A Rahman, B Conroy, S Babaeizadeh
Journal of electrocardiology 51 (6), S18-S21, 2018
Densely Connected Convolutional Networks and Signal Quality Analysis to Detect Atrial Fibrillation Using Short Single-Lead ECG Recordings
J Rubin, S Parvaneh, A Rahman, B Conroy, S Babaeizadeh
arXiv, 2017
Analyzing single-lead short ECG recordings using dense convolutional neural networks and feature-based post-processing to detect atrial fibrillation
S Parvaneh, J Rubin, A Rahman, B Conroy, S Babaeizadeh
Physiological measurement 39 (8), 084003, 2018
A Dynamic Ensemble Approach to Robust Classification in the Presence of Missing Data
B Conroy, L Eshelman, C Potes, M Xu-Wilson
Machine Learning, 1-21, 2015
fMRI-based inter-subject cortical alignment using functional connectivity
B Conroy, B Singer, J Haxby, PJ Ramadge
Advances in Neural Information Processing Systems, 378-386, 2009
Real-time infection prediction with wearable physiological monitoring and AI to aid military workforce readiness during COVID-19
B Conroy, I Silva, G Mehraei, R Damiano, B Gross, E Salvati, T Feng, ...
Scientific reports 12 (1), 3797, 2022
Fast, exact model selection and permutation testing for l2-regularized logistic regression
B Conroy, P Sajda
International Conference on Artificial Intelligence and Statistics, 246-254, 2012
A multimodal encoding model applied to imaging decision-related neural cascades in the human brain
J Muraskin, TR Brown, JM Walz, T Tu, B Conroy, RI Goldman, P Sajda
NeuroImage 180, 211-222, 2018
A clinical prediction model to identify patients at high risk of hemodynamic instability in the pediatric intensive care unit
C Potes, B Conroy, M Xu-Wilson, C Newth, D Inwald, J Frassica
Critical Care 21, 1-8, 2017
Fast Bootstrapping and Permutation Testing for Assessing Reproducibility and Interpretability of Multivariate fMRI Decoding Models
BR Conroy, JM Walz, P Sajda
PloS one 8 (11), e79271, 2013
Fast Bootstrapping and Permutation Testing for Assessing Reproducibility and Interpretability of Multivariate fMRI Decoding Models
B Conroy, J Walz, P Sajda
PLoS ONE 8 (11), e79271, 2013
Early prediction of hemodynamic interventions in the intensive care unit using machine learning
A Rahman, Y Chang, J Dong, B Conroy, A Natarajan, T Kinoshita, ...
Critical Care 25, 1-9, 2021
Learning and applying contextual similarities between entities
B Conroy, M Xu, A Rahman, CMP Blandon
US Patent 11,126,921, 2021
Estimation and use of clinician assessment of patient acuity
LJ Eshelman, ET Carlson, L Yang, XU Minnan, B Conroy
Patient Similarity Using Population Statistics and Multiple Kernel Learning
B Conroy, M Xu-Wilson, A Rahman
Machine Learning for Healthcare (MLHC 2017), 2017
Method and system for monitoring sleep quality
GNG Molina, CMP Blandon, B Conroy, M Xu
US Patent 11,406,323, 2022
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