Machine-learning algorithm to predict hypotension based on high-fidelity arterial pressure waveform analysis F Hatib, Z Jian, S Buddi, C Lee, J Settels, K Sibert, J Rinehart, ... Anesthesiology: The Journal of the American Society of Anesthesiologists 129 …, 2018 | 435 | 2018 |
Development and validation of a deep neural network model for prediction of postoperative in-hospital mortality CK Lee, I Hofer, E Gabel, P Baldi, M Cannesson Anesthesiology: The Journal of the American Society of Anesthesiologists 129 …, 2018 | 170 | 2018 |
Variability in practice and factors predictive of total crystalloid administration during abdominal surgery: retrospective two-centre analysis M Lilot, JM Ehrenfeld, C Lee, B Harrington, M Cannesson, J Rinehart British journal of anaesthesia 114 (5), 767-776, 2015 | 161 | 2015 |
Closed-loop assisted versus manual goal-directed fluid therapy during high-risk abdominal surgery: a case–control study with propensity matching J Rinehart, M Lilot, C Lee, A Joosten, T Huynh, C Canales, D Imagawa, ... Critical Care 19 (1), 94, 2015 | 82 | 2015 |
Closed-loop fluid administration compared to anesthesiologist management for hemodynamic optimization and resuscitation during surgery: an in vivo study J Rinehart, C Lee, C Canales, A Kong, Z Kain, M Cannesson Anesthesia & Analgesia 117 (5), 1119-1129, 2013 | 77 | 2013 |
An automated machine learning-based model predicts postoperative mortality using readily-extractable preoperative electronic health record data BL Hill, R Brown, E Gabel, N Rakocz, C Lee, M Cannesson, P Baldi, ... British Journal of Anaesthesia 123 (6), 877-886, 2019 | 73 | 2019 |
First closed-loop goal directed fluid therapy during surgery: a pilot study J Rinehart, Y Le Manach, H Douiri, C Lee, M Lilot, K Le, C Canales, ... Annales francaises d'anesthesie et de reanimation 33 (3), e35-e41, 2014 | 59 | 2014 |
Big data and targeted machine learning in action to assist medical decision in the ICU R Pirracchio, MJ Cohen, I Malenica, J Cohen, A Chambaz, M Cannesson, ... Anaesthesia Critical Care & Pain Medicine 38 (4), 377-384, 2019 | 57 | 2019 |
Big data and targeted machine learning in action to assist medical decision in the ICU: the past, the present and the future R Pirracchio, M Cohen, I Malenica, J Cohen, A Chambaz, M Canesson, ... | 57* | 2018 |
Closed-loop fluid resuscitation: robustness against weight and cardiac contractility variations J Rinehart, C Lee, M Cannesson, G Dumont Anesthesia & Analgesia 117 (5), 1110-1118, 2013 | 53 | 2013 |
Development and validation of a deep neural network model to predict postoperative mortality, acute kidney injury, and reintubation using a single feature set IS Hofer, C Lee, E Gabel, P Baldi, M Cannesson npj Digital Medicine 3 (1), 1-10, 2020 | 45 | 2020 |
Training and Validation of Deep Neural Networks for the Prediction of 90-Day Post-Liver Transplant Mortality Using UNOS Registry Data BD Ershoff, CK Lee, CL Wray, VG Agopian, G Urban, P Baldi, ... Transplantation Proceedings 52 (1), 246-258, 2020 | 44 | 2020 |
Science Without Conscience Is but the Ruin of the Soul: The Ethics of Big Data and Artificial Intelligence in Perioperative Medicine C Canales, C Lee, M Cannesson Anesthesia & Analgesia 130 (5), 1234-1243, 2020 | 32 | 2020 |
Development and validation of an interpretable neural network for prediction of postoperative in-hospital mortality CK Lee, M Samad, I Hofer, M Cannesson, P Baldi NPJ digital medicine 4 (1), 1-9, 2021 | 31 | 2021 |
Machine learning of physiological waveforms and electronic health record data to predict, diagnose and treat haemodynamic instability in surgical patients: protocol for a … M Cannesson, I Hofer, J Rinehart, C Lee, K Subramaniam, P Baldi, ... BMJ open 9 (12), 2019 | 18 | 2019 |
Comparison of automated vs. manual determination of the respiratory variations in the EKG R wave amplitude for the prediction of fluid responsiveness during surgery CK Lee, J Rinehart, C Canales, M Cannesson Journal of Computational Surgery 1 (1), 5, 2014 | 4 | 2014 |
Preoperative predictions of in-hospital mortality using electronic medical record data B Hill, RP Brown, E Gabel, C Lee, M Cannesson, LO Loohuis, R Johnson, ... bioRxiv, 329813, 2018 | 3 | 2018 |
Goal-directed fluid optimization based on respiratory variations in the pulse oximeter plethysmographic waveform during moderate risk surgery DA Thuraisingham, W Williams, D Ramsingh, KV Le, CK Lee, C Canales, ... Proceedings of the American Society Anesthesiologists, October A 847, 2012 | 3 | 2012 |
Deep Learning for Predicting in Hospital Mortality C Lee, I Hofer, M Cannesson, P Baldi ANESTHESIA AND ANALGESIA 124, 85-86, 2017 | 1 | 2017 |
Use of Big Data and Machine Learning for Prediction of Hypotensive Events in High Risk ICU Patients From the MIMIC II MIT Database CK Lee, M Cannesson, F Hatib ANESTHESIA AND ANALGESIA 122, 2016 | 1* | 2016 |