Raimond L. Winslow, Ph.D.
Affiliations: | Biomedical Engineering | Johns Hopkins University, Baltimore, MD |
Google:
"Raimond Winslow"Mean distance: 14.37 (cluster 17) | S | N | B | C | P |
Cross-listing: Computational Biology Tree
Children
Sign in to add trainee| Jason H. Yang | research assistant | 2003-2006 | Johns Hopkins (Computational Biology Tree) |
| Aagam Shah | research assistant | 2012-2014 | Johns Hopkins (Computational Biology Tree) |
| Peter N. Steinmetz | grad student | 1991-1997 | Johns Hopkins |
| Lisa A. Irvine | grad student | 2000 | Johns Hopkins (Computational Biology Tree) |
| Joseph L. Greenstein | grad student | 2002 | Johns Hopkins (Computational Biology Tree) |
| David F. Scollan | grad student | 2002 | Johns Hopkins (Computational Biology Tree) |
| Charles L. Zimliki | grad student | 2002 | Johns Hopkins (Computational Biology Tree) |
| Patrick A. Helm | grad student | 2005 | Johns Hopkins (Computational Biology Tree) |
| Christina K. Yung | grad student | 2007 | Johns Hopkins (Computational Biology Tree) |
| Tabish Almas | grad student | 2008 | Johns Hopkins (Computational Biology Tree) |
| Yasmin L. Hashambhoy | grad student | 2010 | Johns Hopkins (Computational Biology Tree) |
| Troy Anderson | grad student | 2011 | Johns Hopkins (Computational Biology Tree) |
| Laura Doyle Gauthier | grad student | 2014 | Johns Hopkins (Computational Biology Tree) |
BETA: Related publications
See more...
Publications
|
You can help our author matching system! If you notice any publications incorrectly attributed to this author, please sign in and mark matches as correct or incorrect. |
| Subramaniam S, Akay M, Anastasio MA, et al. (2024) Grand Challenges at the Interface of Engineering and Medicine. Ieee Open Journal of Engineering in Medicine and Biology. 5: 1-13 |
| Jin Q, Greenstein JL, Winslow RL. (2023) Estimating the probability of early afterdepolarizations and predicting arrhythmic risk associated with long QT syndrome type 1 mutations. Biophysical Journal. 122: 4042-4056 |
| Bose SN, Defante A, Greenstein JL, et al. (2023) A data-driven model for early prediction of need for invasive mechanical ventilation in pediatric intensive care unit patients. Plos One. 18: e0289763 |
| Tan Y, Young M, Girish A, et al. (2023) Predicting respiratory decompensation in mechanically ventilated adult ICU patients. Frontiers in Physiology. 14: 1125991 |
| Gong KD, Lu R, Bergamaschi TS, et al. (2022) Predicting Intensive Care Delirium with Machine Learning: Model Development and External Validation. Anesthesiology |
| Wagle N, Morkos J, Liu J, et al. (2022) aEYE: A deep learning system for video nystagmus detection. Frontiers in Neurology. 13: 963968 |
| Ullah A, Hoang-Trong MT, Lederer WJ, et al. (2022) Critical Requirements for the Initiation of a Cardiac Arrhythmia in Rat Ventricle: How Many Myocytes? Cells. 11 |
| Kim HB, Nguyen HT, Jin Q, et al. (2021) Computational Signatures for Post-Cardiac Arrest Trajectory Prediction: Importance of Early Physiological Time Series. Anaesthesia, Critical Care & Pain Medicine. 101015 |
| Annapragada AV, Greenstein JL, Bose SN, et al. (2021) SWIFT: A deep learning approach to prediction of hypoxemic events in critically-Ill patients using SpO2 waveform prediction. Plos Computational Biology. 17: e1009712 |
| Krachman JA, Patricoski JA, Le CT, et al. (2021) Predicting Flow Rate Escalation for Pediatric Patients on High Flow Nasal Cannula Using Machine Learning. Frontiers in Pediatrics. 9: 734753 |