| Reinforcement learning in healthcare: A survey C Yu, J Liu, S Nemati, G Yin ACM Computing Surveys (CSUR) 55 (1), 1-36, 2021 | 724 | 2021 |
| An interpretable machine learning model for accurate prediction of sepsis in the ICU S Nemati, A Holder, F Razmi, MD Stanley, GD Clifford, TG Buchman Critical care medicine 46 (4), 547-553, 2018 | 722 | 2018 |
| Machine learning and decision support in critical care AEW Johnson, MM Ghassemi, S Nemati, KE Niehaus, DA Clifton, ... Proceedings of the IEEE 104 (2), 444-466, 2016 | 435 | 2016 |
| Early prediction of sepsis from clinical data: the PhysioNet/Computing in Cardiology Challenge 2019 MA Reyna, CS Josef, R Jeter, SP Shashikumar, MB Westover, S Nemati, ... Critical care medicine 48 (2), 210-217, 2020 | 380 | 2020 |
| An open source benchmarked toolbox for cardiovascular waveform and interval analysis AN Vest, G Da Poian, Q Li, C Liu, S Nemati, AJ Shah, GD Clifford Physiological measurement 39 (10), 105004, 2018 | 268 | 2018 |
| Quantifying the Ventilatory Control Contribution to Sleep Apnoea Using Polysomnography PI Terrill, BA Edwards, S Nemati, JP Butler, RL Owens, DJ Eckert, ... European Respiratory Journal, 2014 | 264 | 2014 |
| A simplified method for determining phenotypic traits in patients with obstructive sleep apnea A Wellman, BA Edwards, SA Sands, RL Owens, S Nemati, J Butler, ... Journal of applied physiology 114 (7), 911-922, 2013 | 248 | 2013 |
| Optimal medication dosing from suboptimal clinical examples: A deep reinforcement learning approach S Nemati, MM Ghassemi, GD Clifford 2016 38th annual international conference of the IEEE engineering in …, 2016 | 233 | 2016 |
| Early sepsis detection in critical care patients using multiscale blood pressure and heart rate dynamics SP Shashikumar, MD Stanley, I Sadiq, Q Li, A Holder, GD Clifford, ... Journal of electrocardiology 50 (6), 739-743, 2017 | 184 | 2017 |
| A deep learning approach to monitoring and detecting atrial fibrillation using wearable technology SP Shashikumar, AJ Shah, Q Li, GD Clifford, S Nemati 2017 IEEE EMBS international conference on biomedical & health informatics …, 2017 | 179 | 2017 |
| Monitoring and detecting atrial fibrillation using wearable technology S Nemati, MM Ghassemi, V Ambai, N Isakadze, O Levantsevych, A Shah, ... 2016 38th Annual International Conference of the IEEE Engineering in …, 2016 | 164 | 2016 |
| Semisupervised ECG ventricular beat classification with novelty detection based on switching Kalman filters J Oster, J Behar, O Sayadi, S Nemati, AEW Johnson, GD Clifford IEEE Transactions on Biomedical Engineering 62 (9), 2125-2134, 2015 | 149 | 2015 |
| Transfer entropy estimation and directional coupling change detection in biomedical time series J Lee, S Nemati, I Silva, BA Edwards, JP Butler, A Malhotra Biomedical engineering online 11, 1-17, 2012 | 139 | 2012 |
| Data fusion for improved respiration rate estimation S Nemati, A Malhotra, GD Clifford EURASIP journal on advances in signal processing 2010, 1-10, 2010 | 132 | 2010 |
| A Physiological Time Series Dynamics-Based Approach to Patient Monitoring and Outcome Prediction L Lehman, R Adams, L Mayaud, G Moody, A Malhotra, R Mark, S Nemati Biomedical and Health Informatics, 1-1, 2014 | 125* | 2014 |
| Detection of paroxysmal atrial fibrillation using attention-based bidirectional recurrent neural networks SP Shashikumar, AJ Shah, GD Clifford, S Nemati Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018 | 100 | 2018 |
| Biomimetic brain machine interfaces for the control of movement AH Fagg, NG Hatsopoulos, V De Lafuente, KA Moxon, S Nemati, ... Journal of Neuroscience 27 (44), 11842-11846, 2007 | 98 | 2007 |
| Supervised Learning in Dynamic Bayesian Networks S Nemati, RP Adams Neural Information Processing Systems (NIPS) Workshop on Deep Learning and …, 2014 | 97 | 2014 |
| Deep learning in the cross-time frequency domain for sleep staging from a single-lead electrocardiogram Q Li, Q Li, C Liu, SP Shashikumar, S Nemati, GD Clifford Physiological measurement 39 (12), 124005, 2018 | 93 | 2018 |
| Predicting progression to septic shock in the emergency department using an externally generalizable machine-learning algorithm G Wardi, M Carlile, A Holder, S Shashikumar, SR Hayden, S Nemati Annals of emergency medicine 77 (4), 395-406, 2021 | 76 | 2021 |
Gari CliffordProfessor of Biomed Eng & Biomed Inform, Emory University and Georgia Institute of TechnologyVerified email at physionet.org