Shiming Yang

Journal

  1. S. Yang, A. Menne, P.F. Hu, L. Stansbury, C. Gao, N. Dorsey, W. Chiu, S. Shackelford, C.F. Mackenzie, Acoustic Sensor versus Electrocardiographically Derived Respiratory Rate in Unstable Trauma Patients, J. of Clin. Monit. Comput. 2016, accepted on Jun. 3.
  2. N. Parimi, P.F. Hu, C. Mackenzie, S. Yang, et.al, Automated Continuous Vital Signs Predict Use of Uncrossed Matched Blood (UnXRBC) and Massive Transfusioin (MT) Following Trauma, J. of Trauma, 2016;80(6):897-906. Link draft
  3. Z.DW. Dezman, E. Hu, P.F. Hu, S. Yang, L.G. Stansbury, R. Fang, C. Miller, C.F. Mackenzie, Computer Modelling Using Prehospital Vitals Predicts Transfusion and Mortality, Prehospital Emergency Care, Accepted Jan. 2016. Link pdf
  4. S. Yang, P.F. Hu, A. Anazodo, C. Gao, H. Chen, C. Wade, L. Hartsky, C. Miller, C. Imle, R. Fang, C.F. Mackenzie, Trends of hemoglobin oximetry: do they help predict blood transfusion during trauma patient resuscitation?, Anesthesia & Analgesia, 2016; 122(1) p115-25. Link, PrePrint Suppl. Material
  5. B. Bonds, P.F. Hu, Y. Li, S. Yang, K. Colton, A. Gonchigar, J, Cheriyan, T. Grissom, R. Fang, D.M. Stein, Predictive Value of Hyperthermia and Intracranial Hypertension on Neurological Outcomes in Patients with Severe Traumatic Brain Injury, Brain Injury, 2015; 29(13-14):1642-7. DOI: 10.3109/02699052.2015.1075157. Link, pdf
  6. S. Shackelford, S. Yang, P.F. Hu, C. Miller, A. Anazodo, S. Galvagno, Y. Wang, L. Hartsky, R. Fang, C. Mackenzie, Predicting Blood Transfusion using Automated Analysis of Pulse Oximetry Signals and Lab Values, J. of Trauma and Acute Care Surgery, 2015; 79(4) p S175-80. Link, pdf
  7. B.W. Bonds, S. Yang, P.F. Hu, K. Kalpakis, L.G. Stansbury, T.M. Scalea, D.M. Stein, Predicting Secondary Insults After Severe Traumatic Brain Injury: Predicting Intracranial Pressure After Traumatic Brain Injury, J. of Trauma and Acute Care Surgery, 2015, 79(1). link, pdf
  8. S.M. Galvagno, P.F. Hu, S. Yang, C. Gao, D. Hanna, S. Shackelford, C.F. Mackenzie, Accuracy of Continuous Noninvasive Hemoglobin Monitoring for the Prediction of Blood Transfusions in Trauma Patients, J. Clin. Monit. Comput. 2015; accepted for publication on Feb. 23, 2015. link, PDF
  9. K. Kalpakis, S. Yang, P.F. Hu, C. F. Mackenzie, L. Stansbury, D.M. Stein, T.M. Scalea, Permutation entropy analysis of vital signs data for outcome prediction of patients with severe traumatic brain injury, Computers in Biology and Medicine, 2015; 56:167-74. Link PDF.
  10. S. Yang, M. Njoku, C.F. Machenzie, 'Big data' approaches to trauma outcome prediction and autonomous resuscitation, British J. of Hospital Medicine, 2014; 75(11):637-41. Link, draft
  11. K. Colton, S. Yang, P.F. Hu, H.H. Chen, B. Bonds, L.G. Stansbury, T.M. Scalea, D.M. Stein, Pharmacologic Treatment Reduces Pressure Times Time Dose and Relative Duration of Intracranial Hypertension, J. of Intensive Care Medicine, 2014, Oct. 15, doi: 10.1177/0885066614555692. link PDF
  12. K. Colton, S. Yang, P.F. Hu, H.H. Chen, L.G. Stansbury, T.M. Scalea, D.M. Stein, Responsiveness to Therapy for Increased Intracranial Pressure in Traumtic Brain Injury is Associated with Neurological Outcome, Injury, 2014; 45(12):2084-8. link PDF
  13. K. Colton, S. Yang, P.F. Hu, H.H. Chen, B. Bonds, T.M. Scalea, D.M. Stein, Intracranial pressure response after pharmacologic treatment of intracranial hypertension, J. of Trauma and Acute Care Surgery, 77(1):47-53, Jul 2014. link Abstract Preprint
  14. S. Yang, K. Kalpakis, A. Biem, Detecting Road Traffic Events by Coupling Multiple Timeseries with Nonparametric Bayesian Method, IEEE Transactions on Intelligenct Transportation Systems, 2014; 15(5):1936-46. Link. Preprint
  15. C.J. Diamantidis, W. Fink, S. Yang, M.R. Zuckerman, J. Ginsberg, P.Hu, Y. Xiao, and J.C. Fink, Directed Use of the Internet for Health Information by Patients with Chronic Kidney Disease: Prospective Cohort Study, J. of Medical Internet Research, Vol.15, No. 11, p.e251, 2013. link
  16. D. M. Stein, M. Brenner, P.F. Hu, S. Yang, E. C. Hall, L. G. Stansbury, J. Menaker, T. M. Scalea, Timing of Intracranial Hypertension Following Severe Traumatic Brain Injury, J. Neurocritical Care, 2013; 18(3):332-40, Springer. Link, PDF1, PDF2.
  17. D. M. Stein, P. F. Hu, H. Chen, S. Yang, L. G. Stansbury, T.M. Scalea, Computational gene mapping to analyze continuous automated physiologic monitoring data in neuro-trauma intensive care, The Journal of Trauma and Acute Care Surgery, 2012, 73(2):419-25. link
  18. CJ Diamantidis, M Zuckerman, W Fink, Peter Hu, S. Yang, JC Fink, Usability of a CKD Educational Website Targeted to Patients and Their Family Members, Clinical Journal of the American Society of Nephrology, 2012; 7:1-8. link
  19. T. Blattner, S. Yang, Performance study on CUDA GPUs for parallelizing the local ensemble transformed Kalman filter algorithm, Concurrency and Computation: Practice and Experience, 2012; 24(2):167-77, John Wiley & Sons. link, Preprint
  20. S. Yang, MK Gobbert, The optimal relaxation parameter for the SOR method applied to the Poisson equation in any space dimensions, Applied Mathematics Letters 22 (3), 325-331 link, Preprint
  21. S. Yang, T. Huang, A note on estimates for the spectral radius of a nonnegative matrix, Electron. J. Linear Algebra. v13, 352-358 link

Patent

  1. (published) P.Hu, C. Mackenzie, S. Yang, H. Chen, Method and Apparatus for Predicting a Need for a Blood Transfusion, Pub.No.: WO/2015/023708 A1.
UM Ventures

Conference paper (peer-reviewed, full-length)

  1. S. Yang, K. Kalpakis, A. Biem, Spatio-temporal Coupled Bayesian Robust Principal Component Analysis for Road Traffic Event Detection, IEEE Intelligent Transportation Systems (ITSC2013), Oct.6-9, 2013, Hague, Netherland. Abstract Preprint.
  2. S. Chen, S. Yang, K. Kalpakis, Chein-I Chang, Low-rank decomposition-based anomaly detection, SPIE 2013, Baltimore.
  3. S. Yang, K. Kalpakis, Colin F. Mackenzie, Lynn G Stansbury, Deborah M. Stein, Thomas M. Scalea, P. F. Hu, Online Recovery of Missing Values in Vital Signs Data Streams using Low-rank Matrix Completion, 11th International Conference on Machine Learning and Applications ICMLA 2012,pp.281-287, Dec.12-15, Boca Raton, FL Preprint, Abstract
  4. S. Yang, K. Kalpakis, Alain Biem, An Adaptive Observation Site Selection Strategy for Road Traffic Data Assimilation, Fifth ACM SIGSPATIAL International Workshop on Computational Transportation Science, Nov. 6, 2012, Redondo Beach, CA Preprint, Abstract slides
  5. K. Kalpakis, S. Yang, Peter Hu, C. F. Mackenzie, L. Stansbury, D.M. Stein, T.M. Scalea, Outcome Prediction for Patients with Severe Traumatic Brain Injury Using Permutation Entropy Analysis of Electronic Vital Signs Data, Machine Learning and Data Mining in Pattern Recognition, 415-426 (Nominated Best Paper.) link, Preprint, Abstract slides
  6. MK Gobbert, S. Yang, Numerical demonstration of finite element convergence for Lagrange elements in COMSOL Multiphysics, In: Vineet Dravid, editor, Proceedings of the COMSOL Conference 2008, Boston, MA. Preprint, slides

Abstract

  1. M. J. Bradley, B. Bonds, L. Chang, S. Yang, P. Hu, H.C. Li, M.L. Brenner, T.M. Scalea, D.M. Stein, Open Chest Cardiac Massage Offers No Benefit Over Closed Chest Compressions in Patients with Trauma Cardiac Arrest, 29th EAST Annual Scientific Assembly, Jan. 12-16, 2016, San Antonio, Texas.
  2. P. Hu, S. Shackelford, S. Yang, H.C. Li, D. M. Stein, T.M. Scalea, C.F. Mackenzie, Do Multiple Vital Sign Sensors Improve the Prediction of Emergency Blood Transfusion in Adult Trauma Patients? Millitary Health System Research Symposium (MHSRS) 2015, Aug.17-20, Ft. Lauderdale, FL.
  3. P. Hu, S. Yang, F. Yang, H.C. Li, G. Hagegeorge, L. Hartsky, C. Miller, B. Bonds, C.F. Mackenzie, Big Data Challenge: How Much Redundance is Required in Real-time Trauma Patient Vital Signs Waveform Collecting System? Millitary Health System Research Symposium (MHSRS) 2015, Aug.17-20, Ft. Lauderdale, FL.
  4. D.M. Stein, P. Hu, S. Yang, et. al, An Early Decision Model Predicts the Need for Uncross Matched Blood (UnXRBC) and Massive Transfusion (MT) Following Trauma, the 74th Annual Meeting of AAST and Clinical Congress of Acute Care Surgery, Las Vegas, NV, Sep.9-12, 2015.
  5. K. Colton, S. Yang, P. Hu, T. M. Scalea, D. M. Stein, Simplifying the calculation of optimal cerebral perfusion pressure without continuous waveforms, Society of Critical Care Congress (SCCM) 2015, Phonenix, Arizona, Jan.17-21, 2015.
  6. C. Mackenzie, G. Cheng, A. Ananzada, H.H. Chen, S. Yang, R. Fang, S. Galvagno, P. Hu, Are hemoglobin oximetry, vital signs and laboratory values able to predict emergency transfusion? Society of Critical Care Congress (SCCM) 2015, Phonenix, Arizona, Jan.17-21, 2015.
  7. K. Colton, S. Yang, P. Hu, H.H. Chen, T.M. Scalea, D. M. Stein, Hemodynamic changes after decompressive craniectomy for intracranial hypertension, Society of Critical Care Congress (SCCM) 2015, Phonenix, Arizona, Jan.17-21, 2015.
  8. S. Yang, P. Hu, Y. Wang, A. Anazado, C. Miller, R. Fang, S. Shackelford, C. Mackenzie, Design of Vendor-neutral Platform for Fast Prototype Model Verification and Deployment, AMIA Annual Symposium 2014, Nov. 14-18, D.C.
  9. P. Hu, R. Ramakrishnan, S. Yang, A. Anazodo, C. Imle, L. Hartsky, C. Miller, S. Shackelford, S. Galvagno, J.D.O., C. Mackenzie, Do multiple measurements of field vital signs enhance prediction of emergency transfusion and interventions?, ASA (Anesthesiology) 2014, New Orleans, LA, Oct.11-15. abstract
  10. B. Bonds, P. Hu, Y. Li, S. Yang, K. Colton, T. Grisson, R. Fang, D. Stein, Predicive Value of Hyperthermia and Intracranial Hypertension on Neurological Outcomes in Patients with Moderate to Severe Traumatic Brain Injury, International Brain Injury Association(IBIA), San Francisco, Mar. 19-22, 2014.
  11. K. Colton, S. Yang, P. Hu, H. Chen, L. Stansbury, T.M. Scalea, D.M. Stein, Intracranial Pressure Response After Pharmacologic Treatment of Intracranial Hypertension. 27th Eastern Association for the Surgery of Trauma (EAST) Annual Scientific Assembly, Jan. 14-18, 2014.
  12. K. Colton, S. Yang, P. Hu, L. Stansbury, H. H. Chen, Thomas M. Scalea, Deborah Stein, Responsiveness to Therapy for Increased Intracranial Pressure in Traumatic Brain Injury is Associated with Neurological Outcome, J. of Neurotrauma, 30 (15), A123-A124. link
  13. H. H. Chen, S. Yang, P. Hu, L. G. Stansbury, Catriona Miller, Deborah M. Stein, T. M. Scalea, Logistic Regression Modeling as an Analytic Platform to Provide Valid Individualized Prognostic Information from Continuous Realtime Monitoring Data in the Neuro-trauma Critical Care Unit, J. of Neurotrauma, 30 (15), A126-A126. link
  14. R. North, P.F.Hu, S. Yang, K. Frank, C.F. Mackenzie, Real-world Respiratory Rate (RR) Signal Processing During Trauma Patient Resuscitation. AMIA 2013, D.C. link
  15. P. F. Hu, Colin F. Mackenzie, L. G. Stansbury, S. Yang, X. Zhu, JR Hess, & ONPOINT Group, Gender- and age-adjusted Shock Index predictions of emergent blood use. Military Health System Research Symposium (MHSRS)/ATACCC Aug 13-16 2012
  16. P. Hu, M. Zuckerman, W Fink, S. Yang, J. Fink, Design and Development of a Patient Safety Website for Tracking Chronic Kidney Disease Patients, American Telemedicine Association, 16th Annual International Meeting & Exposition, May 1-3, 2012, Tampa, Florida
  17. K. Kalpakis, S. Yang, Y. Yesha, Near Real-time Data Assimilation for the HYSPLIT Aerosol Dispersion Model, AGU Fall Meeting Abstracts link

Other (Report, Thesis)

  1. S. Yang, On Prediction and Estimation for Datastreams Utilizing Sparsity and Structure, PhD Dissertation, 2013. Advisor: Dr. K. Kalpakis. Abstract
  2. K. Kalpakis, S. Yang, Y. Yesha, Improving HYSPLIT Particle Dispersion Prediction with Data Assimilation, Technical Report TR2010', University of Maryland, Baltimore County Preprint
  3. S. Yang, MK Gobbert, Convergence Order Studies for Elliptic Test Problems with COMSOL Multiphysics, TR-HPCF-2008-4, UMBC High Performance Computing Facility, UMBC, 2008 PDF
  4. S. Yang, MK Gobbert, The optimal relaxation parameter for the SOR method applied to a classical model problem, Technical Report TR2007', University of Maryland, Baltimore County link

Review

I served as reviewer for the following journals/conferences:

  1. International Conference on Intelligent Computing (ICIC2016)
  2. Statistical Methods in Medical Research
  3. Neurocomputing (Elsevier)
  4. Healthcare, MDPI
  5. Society for Academic Emergency Medicine Annual Meeting 2016
  6. IEEE BigdataService 2016
  7. IEEE Trans. on Vehicular Technology
  8. AMIA (American Medical Informatics Association) 2014,2015,2016 Annual Symposium
  9. Computers in Biology and Medicine
  10. Currency and Computation

Some presentations

  1. Learning from Clinical Data 150th Method and Stat Meeting of Patient Safety Research Group, UMB, Aug. 12, 2014. slides
  2. A short talk on machine learning: on the Method and Stat Meeting of Patient Safety Research Group, UMB, Aug. 5, 2014. slides
  3. A short talk on variable importance: on the Method and Stat Meeting of Patient Safety Research Group, UMB, Jul. 29, 2014. slides
  4. Massive Clinical Data Analyzing: How Clinical Research Meets the Big Data. Univ. of Maryland School of Medicine, Department of Anesthesiology, Jan. 30, 2014. slides
  5. Road Traffic Forecast: On Model Calibration and Solving. UMBC, Mar. 27, 2012. slides
  6. Graphical Model and Partical Filtering. UMBC. Apr. 11, 2011. slides


Last updated on Jul. 22, 2015.