| 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 | 742 | 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 | 385 | 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 | 197 | 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 | 130 | 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 | 89 | 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 | 64 | 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 | 56 | 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 | 55 | 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 | 53 | 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 | 48 | 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 | 44 | 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 | 34 | 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 | 34 | 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 | 26 | 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 | 26 | 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 | 22 | 2021 |
| Learning and applying contextual similarities between entities B Conroy, M Xu, A Rahman, CMP Blandon US Patent 11,126,921, 2021 | 10 | 2021 |
| Estimation and use of clinician assessment of patient acuity LJ Eshelman, ET Carlson, L Yang, XU Minnan, B Conroy | 9 | 2017 |
| Patient Similarity Using Population Statistics and Multiple Kernel Learning B Conroy, M Xu-Wilson, A Rahman Machine Learning for Healthcare (MLHC 2017), 2017 | 7 | 2017 |
| Method and system for monitoring sleep quality GNG Molina, CMP Blandon, B Conroy, M Xu US Patent 11,406,323, 2022 | 6 | 2022 |
Asif RahmanSenior Scientist, AppleVerified email at apple.com
