| Combining multiple QEEG features to estimate drug-independent sedation level using machine learning SB Nagaraj, SM Ramaswamy, MMR Struys US Patent 12,076,159, 2024 | 339 | 2024 |
| Quantitative EEG reactivity and machine learning for prognostication in hypoxic-ischemic brain injury E Amorim, M Van der Stoel, SB Nagaraj, MM Ghassemi, J Jing, ... Clinical neurophysiology 130 (10), 1908-1916, 2019 | 90 | 2019 |
| Machine‐learning–based early prediction of end‐stage renal disease in patients with diabetic kidney disease using clinical trials data S Belur Nagaraj, MJ Pena, W Ju, HL Heerspink, BEAt‐DKD Consortium Diabetes, Obesity and Metabolism 22 (12), 2479-2486, 2020 | 57 | 2020 |
| STQS: Interpretable multi-modal Spatial-Temporal-seQuential model for automatic Sleep scoring S Pathak, C Lu, SB Nagaraj, M van Putten, C Seifert Artificial intelligence in medicine 114, 102038, 2021 | 55 | 2021 |
| Patient-specific classification of ICU sedation levels from heart rate variability SB Nagaraj, S Biswal, EJ Boyle, DW Zhou, LM McClain, EK Bajwa, ... Critical care medicine 45 (7), e683-e690, 2017 | 48 | 2017 |
| Automatic classification of sedation levels in ICU patients using heart rate variability SB Nagaraj, LM McClain, DW Zhou, S Biswal, ES Rosenthal, PL Purdon, ... Critical care medicine 44 (9), e782-e789, 2016 | 47 | 2016 |
| A metabolomics‐based molecular pathway analysis of how the sodium‐glucose co‐transporter‐2 inhibitor dapagliflozin may slow kidney function decline in patients with diabetes S Mulder, A Hammarstedt, SB Nagaraj, V Nair, W Ju, J Hedberg, ... Diabetes, Obesity and Metabolism 22 (7), 1157-1166, 2020 | 46 | 2020 |
| Neonatal seizure detection using atomic decomposition with a novel dictionary SB Nagaraj, NJ Stevenson, WP Marnane, GB Boylan, G Lightbody IEEE Transactions on Biomedical Engineering 61 (11), 2724-2732, 2014 | 41 | 2014 |
| The revised Cerebral Recovery Index improves predictions of neurological outcome after cardiac arrest SB Nagaraj, MC Tjepkema-Cloostermans, BJ Ruijter, J Hofmeijer, ... Clinical neurophysiology 129 (12), 2557-2566, 2018 | 40 | 2018 |
| The Neu-Prem Trial: neuromonitoring of brains of infants born preterm during resuscitation—a prospective observational cohort study AC Katheria, MJ Harbert, SB Nagaraj, K Arnell, DM Poeltler, MK Brown, ... The Journal of pediatrics 198, 209-213. e3, 2018 | 39 | 2018 |
| Automated tracking of level of consciousness and delirium in critical illness using deep learning H Sun, E Kimchi, O Akeju, SB Nagaraj, LM McClain, DW Zhou, E Boyle, ... NPJ digital medicine 2 (1), 89, 2019 | 37 | 2019 |
| Electroencephalogram based detection of deep sedation in ICU patients using atomic decomposition SB Nagaraj, LM McClain, EJ Boyle, DW Zhou, SM Ramaswamy, S Biswal, ... IEEE Transactions on Biomedical Engineering 65 (12), 2684-2691, 2018 | 36 | 2018 |
| Dexmedetomidine-induced deep sedation mimics non-rapid eye movement stage 3 sleep: large-scale validation using machine learning SM Ramaswamy, MAS Weerink, MMRF Struys, SB Nagaraj Sleep 44 (2), zsaa167, 2021 | 35 | 2021 |
| Predicting short‐and long‐term glycated haemoglobin response after insulin initiation in patients with type 2 diabetes mellitus using machine‐learning algorithms SB Nagaraj, G Sidorenkov, JFM van Boven, P Denig Diabetes, Obesity and Metabolism 21 (12), 2704-2711, 2019 | 34 | 2019 |
| Novel drug-independent sedation level estimation based on machine learning of quantitative frontal electroencephalogram features in healthy volunteers SM Ramaswamy, MH Kuizenga, MAS Weerink, HEM Vereecke, ... British Journal of Anaesthesia 123 (4), 479-487, 2019 | 25 | 2019 |
| Predicting deep hypnotic state from sleep brain rhythms using deep learning: A data-repurposing approach SB Nagaraj, SM Ramaswamy, MAS Weerink, MMRF Struys Anesthesia & Analgesia 130 (5), 1211-1221, 2020 | 21 | 2020 |
| Brain monitoring of sedation in the intensive care unit using a recurrent neural network H Sun, SB Nagaraj, O Akeju, PL Purdon, BM Westover 2018 40th Annual International Conference of the IEEE Engineering in …, 2018 | 20 | 2018 |
| Identifying patients at increased risk of hypoglycaemia in primary care: Development of a machine learning‐based screening tool S Crutzen, S Belur Nagaraj, K Taxis, P Denig Diabetes/Metabolism Research and Reviews 37 (7), e3426, 2021 | 10 | 2021 |
| ADARRI: a novel method to detect spurious R-peaks in the electrocardiogram for heart rate variability analysis in the intensive care unit DJ Rebergen, SB Nagaraj, ES Rosenthal, MT Bianchi, MJAM van Putten, ... Journal of clinical monitoring and computing 32, 53-61, 2018 | 10 | 2018 |
| Robustness of time frequency distribution based features for automated neonatal EEG seizure detection SB Nagaraj, NJ Stevenson, WP Marnane, GB Boylan, G Lightbody 2014 36th Annual International Conference of the IEEE Engineering in …, 2014 | 9 | 2014 |
M. Brandon Westover, MD, PhDHarvard Medical School / Massachusetts General HospitalVahvistettu sähköpostiosoite verkkotunnuksessa mgh.harvard.edu