| 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 | 756 | 2018 |
| Fluid response evaluation in sepsis hypotension and shock: a randomized clinical trial IS Douglas, PM Alapat, KA Corl, MC Exline, LG Forni, AL Holder, ... Chest 158 (4), 1431-1445, 2020 | 237 | 2020 |
| Analysis of discrepancies between pulse oximetry and arterial oxygen saturation measurements by race and ethnicity and association with organ dysfunction and mortality AKI Wong, M Charpignon, H Kim, C Josef, AAH De Hond, JJ Fojas, ... JAMA network open 4 (11), e2131674-e2131674, 2021 | 196 | 2021 |
| 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 | 187 | 2017 |
| Predictors of early progression to severe sepsis or shock among emergency department patients with nonsevere sepsis AL Holder, N Gupta, E Lulaj, M Furgiuele, I Hidalgo, MP Jones, T Jolly, ... International Journal of Emergency Medicine 9, 1-11, 2016 | 87 | 2016 |
| 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 | 86 | 2021 |
| eARDS: A multi-center validation of an interpretable machine learning algorithm of early onset Acute Respiratory Distress Syndrome (ARDS) among critically ill adults with COVID-19 L Singhal, Y Garg, P Yang, A Tabaie, AI Wong, A Mohammed, L Chinthala, ... PloS one 16 (9), e0257056, 2021 | 41 | 2021 |
| Using what you get: dynamic physiologic signatures of critical illness AL Holder, G Clermont Critical care clinics 31 (1), 133, 2015 | 28 | 2015 |
| Leveraging clinical data across healthcare institutions for continual learning of predictive risk models F Amrollahi, SP Shashikumar, AL Holder, S Nemati Scientific reports 12 (1), 8380, 2022 | 25 | 2022 |
| Machine learning methods to predict acute respiratory failure and acute respiratory distress syndrome AKI Wong, PC Cheung, R Kamaleswaran, GS Martin, AL Holder Frontiers in big Data 3, 579774, 2020 | 24 | 2020 |
| Serial daily organ failure assessment beyond ICU day 5 does not independently add precision to ICU risk-of-death prediction AL Holder, E Overton, P Lyu, JA Kempker, S Nemati, F Razmi, GS Martin, ... Critical care medicine 45 (12), 2014-2022, 2017 | 22 | 2017 |
| A locally optimized data-driven tool to predict sepsis-associated vasopressor use in the ICU AL Holder, SP Shashikumar, G Wardi, TG Buchman, S Nemati Critical care medicine 49 (12), e1196-e1205, 2021 | 20 | 2021 |
| Inhaled carbon monoxide protects against the development of shock and mitochondrial injury following hemorrhage and resuscitation H Gomez, B Kautza, D Escobar, I Nassour, J Luciano, AM Botero, ... PLoS One 10 (9), e0135032, 2015 | 20 | 2015 |
| Design, implementation, and validation of a pediatric ICU sepsis prediction tool as clinical decision support M Dewan, R Vidrine, M Zackoff, Z Paff, B Seger, S Pfeiffer, P Hagedorn, ... Applied Clinical Informatics 11 (02), 218-225, 2020 | 18 | 2020 |
| Effects of inhalation of low-dose nitrite or carbon monoxide on post-reperfusion mitochondrial function and tissue injury in hemorrhagic shock swine H Haugaa, H Gómez, DR Maberry, A Holder, O Ogundele, AMB Quintero, ... Critical Care 19, 1-12, 2015 | 17 | 2015 |
| A dream deferred: the rise and fall of recombinant activated protein C AL Holder, DT Huang Critical Care 17, 1-3, 2013 | 15 | 2013 |
| Coronavirus disease 2019 temperature trajectories correlate with hyperinflammatory and hypercoagulable subphenotypes SV Bhavani, PA Verhoef, CL Maier, C Robichaux, WF Parker, A Holder, ... Critical Care Medicine 50 (2), 212-223, 2022 | 14 | 2022 |
| Applied physiology at the bedside to drive resuscitation algorithms AL Holder, MR Pinsky Journal of cardiothoracic and vascular anesthesia 28 (6), 1642, 2014 | 14 | 2014 |
| The big consequences of small discrepancies: why racial differences in pulse oximetry errors matter AL Holder, AKI Wong Critical care medicine 50 (2), 335-337, 2022 | 13 | 2022 |
| A FHIR-enabled streaming sepsis prediction system for ICUs JR Henry, D Lynch, J Mals, SP Shashikumar, A Holder, A Sharma, ... 2018 40th annual international conference of the IEEE engineering in …, 2018 | 13 | 2018 |