| A call to alarms: current state and future directions in the battle against alarm fatigue M Hravnak, T Pellathy, L Chen, A Dubrawski, A Wertz, G Clermont, ... Journal of electrocardiology 51 (6), S44-S48, 2018 | 81 | 2018 |
| Liquid crystal elastomer with integrated soft thermoelectrics for shape memory actuation and energy harvesting M Zadan, DK Patel, AP Sabelhaus, J Liao, A Wertz, L Yao, C Majidi Advanced Materials 34 (23), 2200857, 2022 | 59 | 2022 |
| The critical care data exchange format: a proposed flexible data standard for combining clinical and high-frequency physiologic data in critical care P Laird, A Wertz, G Welter, D Maslove, A Hamilton, JH Yoon, DE Lake, ... Physiological Measurement 42 (6), 065002, 2021 | 12 | 2021 |
| Parsimony of hemodynamic monitoring data sufficient for the detection of hemorrhage MR Pinsky, A Wertz, G Clermont, A Dubrawski Anesthesia & Analgesia 130 (5), 1176-1187, 2020 | 12 | 2020 |
| Increasing cardiovascular data sampling frequency and referencing it to baseline improve hemorrhage detection A Wertz, AL Holder, M Guillame-Bert, G Clermont, A Dubrawski, ... Critical Care Explorations 1 (10), e0058, 2019 | 9 | 2019 |
| In-situ sensing and dynamics predictions for electrothermally-actuated soft robot limbs AP Sabelhaus, RK Mehta, AT Wertz, C Majidi Frontiers in Robotics and AI 9, 888261, 2022 | 8 | 2022 |
| Trajectory optimization for thermally-actuated soft planar robot limbs A Wertz, AP Sabelhaus, C Majidi 2022 IEEE 5th International Conference on Soft Robotics (RoboSoft), 439-446, 2022 | 7 | 2022 |
| Safe Supervisory Control of Soft Robot Actuators AP Sabelhaus, ZJ Patterson, AT Wertz, C Majidi Soft Robotics, 2024 | 4 | 2024 |
| Detecting Patterns of Physiological Response to Hemodynamic Stress via Unsupervised Deep Learning C Gao, F Falck, M Goswami, A Wertz, MR Pinsky, A Dubrawski arXiv preprint arXiv:1911.05121, 2019 | 3 | 2019 |
| Genome Sequence of Gordonia Phage BetterKatz WH Pope, EN Berryman, KM Forrest, L McHale, AT Wertz, Z Zhuang, ... Genome Announcements 4 (4), 10.1128/genomea. 00590-16, 2016 | 1 | 2016 |
| Continuous Intraoperative Data Analysis Using Machine Learning Reveals Multiple Parameters to Predict Post-CABG Renal Failure W Potosnak The Society of Thoracic Surgeons Annual Meeting, 2021 | | 2021 |
| Robustness of Machine Learning Models for Hemorrhage Detection V Jeanselme, A Wertz, G Clermont, MR Pinsky, A Dubrawski D23. WHAT'S NEW IN NON-PULMONARY CRITICAL CARE?, A6320-A6320, 2020 | | 2020 |
| 1257: BINARIZED SEVERITY LEVEL OF FUTURE INSTABILITY RISK IN CONTINUOUSLY MONITORED PATIENTS L Chen, A Dubrawski, G Clermont, T Pellathy, A Wertz, JH Yoon, M Pinsky, ... Critical Care Medicine 47 (1), 605, 2019 | | 2019 |
| 38: SUFFICIENT SAMPLING FREQUENCY FOR MACHINE LEARNING TO SEPARATE MONITORING ARTIFACT FROM INSTABILITY A Wertz, M Hravnak, A Dubrawski, L Chen, T Pellathy, G Clermont, ... Critical Care Medicine 46 (1), 19, 2018 | | 2018 |
