Raimond L. Winslow, Ph.D.

Biomedical Engineering Johns Hopkins University, Baltimore, MD 
"Raimond Winslow"
Mean distance: 14.37 (cluster 17)
Cross-listing: Computational Biology Tree


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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)
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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
Jin Q, Greenstein JL, Winslow RL. (2021) Estimating ectopic beat probability with simplified statistical models that account for experimental uncertainty. Plos Computational Biology. 17: e1009536
Bose SN, Greenstein JL, Fackler JC, et al. (2021) Early Prediction of Multiple Organ Dysfunction in the Pediatric Intensive Care Unit. Frontiers in Pediatrics. 9: 711104
Liu R, Greenstein JL, Fackler JC, et al. (2021) Prediction of Impending Septic Shock in Children With Sepsis. Critical Care Explorations. 3: e0442
Annapragada AV, Greenstein JL, Bose SN, et al. (2021) SWIFT: A Deep Learning Approach to Prediction of Hypoxemic Events in Critically-Ill Patients Using SpO Waveform Prediction. Medrxiv : the Preprint Server For Health Sciences
Liu R, Greenstein JL, Fackler JC, et al. (2020) Spectral clustering of risk score trajectories stratifies sepsis patients by clinical outcome and interventions received. Elife. 9
Jin Q, Greenstein JL, Winslow RL. (2020) Simplified Models Predict Cellular Arrhythmia Probabilities and Reveal the Impact of Experimental Parameter Uncertainty on the Predicted Distribution of Arrhythmic Events Biophysical Journal. 118: 409a
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