Shiming Yang, Ph.D.
Affiliations: | 2013 | Computer Science | University of Maryland, Baltimore County, Baltimore, MD, United States |
Area:
Computer ScienceGoogle:
"Shiming Yang"Parents
Sign in to add mentor| Konstantinos Kalpakis | grad student | 2013 | UMBC | |
| (On Prediction and Estimation for Datastreams Utilizing Sparsity and Structure.) | ||||
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Publications
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| Crawford AM, Yang S, Hu P, et al. (2019) Concomitant chest trauma and traumatic brain injury, biomarkers correlate with worse outcomes. The Journal of Trauma and Acute Care Surgery. 87: S146-S151 |
| Melinosky C, Yang S, Hu P, et al. (2018) Continuous Vital Sign Analysis to Predict Secondary Neurological Decline After Traumatic Brain Injury. Frontiers in Neurology. 9: 761 |
| Hu PF, Yang S, Li HC, et al. (2017) Reliable Collection of Real-Time Patient Physiologic Data from less Reliable Networks: a "Monitor of Monitors" System (MoMs). Journal of Medical Systems. 41: 3 |
| Dezman ZD, Gao C, Yang S, et al. (2016) Anomaly Detection Outperforms Logistic Regression in Predicting Outcomes in Trauma Patients. Prehospital Emergency Care : Official Journal of the National Association of Ems Physicians and the National Association of State Ems Directors. 1-6 |
| Yang S, Menne A, Hu P, et al. (2016) Acoustic sensor versus electrocardiographically derived respiratory rate in unstable trauma patients. Journal of Clinical Monitoring and Computing |
| Parimi N, Yang S, Hu PF, et al. (2016) Noninvasive Prediction of Neuroworsening in Patints with Traumatic Brain Injury Journal of the American College of Surgeons. 223: e93-e94 |
| Bonds BW, Hu P, Li Y, et al. (2015) Predictive value of hyperthermia and intracranial hypertension on neurological outcomes in patients with severe traumatic brain injury. Brain Injury. 1-6 |
| Bonds BW, Yang S, Hu PF, et al. (2015) Predicting secondary insults after severe traumatic brain injury. The Journal of Trauma and Acute Care Surgery. 79: 85-90 |
| Galvagno SM, Hu P, Yang S, et al. (2015) Accuracy of continuous noninvasive hemoglobin monitoring for the prediction of blood transfusions in trauma patients. Journal of Clinical Monitoring and Computing |
| Kalpakis K, Yang S, Hu PF, et al. (2015) Permutation entropy analysis of vital signs data for outcome prediction of patients with severe traumatic brain injury. Computers in Biology and Medicine. 56: 167-74 |