Vital-sign Data Fusion Models for Post-operative Patients
暂无分享,去创建一个
David A. Clifton | Lionel Tarassenko | Lei A. Clifton | Peter J. Watkinson | Marco A. F. Pimentel | L. Tarassenko | D. Clifton | P. Watkinson | M. Pimentel
[1] Bernhard Schölkopf,et al. Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra , 2000, NIPS.
[2] L. Tarassenko,et al. Chapter 35 Novelty Detection , 2009 .
[3] M. Hravnak,et al. Defining the incidence of cardiorespiratory instability in patients in step-down units using an electronic integrated monitoring system. , 2008, Archives of internal medicine.
[4] J. Ickovics,et al. Psychosocial Factors and Surgical Outcomes: An Evidence‐Based Literature Review , 2006, The Journal of the American Academy of Orthopaedic Surgeons.
[5] M. Singer,et al. Unexpected Deaths and Referrals to Intensive Care of Patients on General Wards – Are Some Cases Potentially Avoidable? , 1999, Journal of the Royal College of Physicians of London.
[6] Radford M. Neal. Pattern Recognition and Machine Learning , 2007, Technometrics.
[7] Les E. Atlas,et al. Hidden Markov models for monitoring machining tool-wear , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).
[8] L. Forni,et al. Worthing physiological scoring system: derivation and validation of a physiological early-warning system for medical admissions. An observational, population-based single-centre study. , 2007, British journal of anaesthesia.
[9] B. Baxter,et al. Temporal patterns of postoperative complications. , 2003, Archives of surgery.
[10] L. Tarassenko,et al. Novelty detection in jet engines , 1999 .
[11] Bernhard Schölkopf,et al. Support Vector Method for Novelty Detection , 1999, NIPS.
[12] Graham J. Williams,et al. On-Line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms , 2000, KDD '00.
[13] Tom Fawcett,et al. ROC Graphs: Notes and Practical Considerations for Researchers , 2007 .
[14] Gary B. Smith,et al. ViEWS--Towards a national early warning score for detecting adult inpatient deterioration. , 2010, Resuscitation.
[15] L. Tarassenko,et al. Centile-based early warning scores derived from statistical distributions of vital signs. , 2011, Resuscitation.
[16] K. Hillman,et al. The objective medical emergency team activation criteria: a case-control study. , 2007, Resuscitation.
[17] R G Mark,et al. Robust heart rate estimation from multiple asynchronous noisy sources using signal quality indices and a Kalman filter , 2008, Physiological measurement.
[18] John W. Sammon,et al. A Nonlinear Mapping for Data Structure Analysis , 1969, IEEE Transactions on Computers.
[19] Giles Morgan,et al. Confidential inquiry into quality of care before admission to intensive care , 1998, BMJ.
[20] L. Tarassenko,et al. Bayesian Extreme Value Statistics for Novelty Detection in Gas-Turbine Engines , 2008, 2008 IEEE Aerospace Conference.
[21] T. Hodgetts,et al. Incidence, location and reasons for avoidable in-hospital cardiac arrest in a district general hospital. , 2002, Resuscitation.
[22] David R Prytherch,et al. A review, and performance evaluation, of single-parameter "track and trigger" systems. , 2008, Resuscitation.
[23] D. Harrison,et al. Systematic review and evaluation of physiological track and trigger warning systems for identifying at-risk patients on the ward , 2007, Intensive Care Medicine.
[24] Marilyn Hravnak,et al. Cardiorespiratory instability before and after implementing an integrated monitoring system* , 2011, Critical care medicine.
[25] Michael Buist,et al. Association between clinically abnormal observations and subsequent in-hospital mortality: a prospective study. , 2004, Resuscitation.
[26] Joachim Denzler,et al. One-class classification with Gaussian processes , 2013, Pattern Recognit..
[27] F. Ismail,et al. Integrated monitoring and analysis for early warning of patient deterioration. , 2007, British journal of anaesthesia.
[28] Brian H Cuthbertson,et al. Can physiological variables and early warning scoring systems allow early recognition of the deteriorating surgical patient?* , 2007, Critical care medicine.
[29] Germano C. Vasconcelos,et al. Investigating feedforward neural networks with respect to the rejection of spurious patterns , 1995, Pattern Recognit. Lett..
[30] Sameer Singh,et al. Novelty detection: a review - part 1: statistical approaches , 2003, Signal Process..
[31] Lionel Tarassenko,et al. BIOSIGN™ : multi-parameter monitoring for early warning of patient deterioration , 2005 .
[32] J. Légaré,et al. ICU readmission after cardiac surgery. , 2003, European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery.
[33] M. Tivey,et al. Prospective evaluation of a modified Early Warning Score to aid earlier detection of patients developing critical illness on a general surgical ward , 2000 .
[34] Yuxin Ding,et al. Host-based intrusion detection using dynamic and static behavioral models , 2003, Pattern Recognit..
[35] R. Veldhuis. The centroid of the symmetrical Kullback-Leibler distance , 2002, IEEE Signal Processing Letters.
[36] B. Waxman,et al. Recognising clinical instability in hospital patients before cardiac arrest or unplanned admission to intensive care: A pilot study in a tertiary‐care hospital , 1999, The Medical journal of Australia.
[37] G. Moore,et al. Effects of a medical emergency team on reduction of incidence of and mortality from unexpected cardiac arrests in hospital: preliminary study , 2002, BMJ : British Medical Journal.
[38] K. Hillman,et al. Duration of life-threatening antecedents prior to intensive care admission , 2002, Intensive Care Medicine.
[39] K. Hillman,et al. A comparison of Antecedents to Cardiac Arrests, Deaths and EMergency Intensive care Admissions in Australia and New Zealand, and the United Kingdom—the ACADEMIA study , 2004 .
[40] Valerie J. Gooder,et al. Inpatient transfers to the intensive care unit , 2003 .
[41] Christopher M. Bishop,et al. Novelty detection and neural network validation , 1994 .
[42] Y. van der Graaf,et al. Prediction of serious complications in patients admitted to a surgical ward , 2002, The British journal of surgery.
[43] Michael Brady,et al. Novelty detection for the identification of masses in mammograms , 1995 .
[44] Paul E. Schmidt,et al. Review and performance evaluation of aggregate weighted 'track and trigger' systems. , 2008, Resuscitation.
[45] C. Subbe,et al. Validation of a modified Early Warning Score in medical admissions. , 2001, QJM : monthly journal of the Association of Physicians.
[46] Worthington,et al. The patient‐at‐risk team: identifying and managing seriously ill ward patients , 1999, Anaesthesia.
[47] David A. Clifton,et al. Novelty Detection for Identifying Deterioration in Emergency Department Patients , 2011, IDEAL.
[48] E. Draper,et al. APACHE II: A severity of disease classification system , 1985, Critical care medicine.
[49] M. Odell,et al. An acute problem? A report of the National Confidential Enquiry into Patient Outcome and Death. , 2005, Nursing in critical care.
[50] P. Sajda,et al. Detection, synthesis and compression in mammographic image analysis with a hierarchical image probability model , 2001, Proceedings IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA 2001).
[51] Huaiyu Zhu. On Information and Sufficiency , 1997 .
[52] Christopher K. I. Williams,et al. Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning) , 2005 .
[53] Ian T. Nabney,et al. Netlab: Algorithms for Pattern Recognition , 2002 .
[54] Sameer Singh,et al. Novelty detection: a review - part 2: : neural network based approaches , 2003, Signal Process..
[55] G.B. Moody,et al. Robust parameter extraction for decision support using multimodal intensive care data , 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[56] Jim Austin,et al. Novelty detection for strain-gauge degradation using maximally correlated components , 2002, ESANN.
[57] D. Brillinger,et al. Handbook of methods of applied statistics , 1967 .
[58] J. Bion,et al. Outcomes in intensive care. , 1993, BMJ.
[59] S. Roberts. EXTREME VALUE STATISTICS FOR NOVELTY DETECTION IN BIOMEDICAL DATA PROCESSING , 2000 .
[60] L. Tarassenko,et al. BIOSIGN/spl trade/ : multi-parameter monitoring for early warning of patient deterioration , 2005 .
[61] Stephen J. Roberts,et al. A Probabilistic Resource Allocating Network for Novelty Detection , 1994, Neural Computation.
[62] A. McGinley,et al. A physiologically‐based early warning score for ward patients: the association between score and outcome * , 2005, Anaesthesia.
[63] D Young,et al. Suboptimal care of patients before admission to intensive care , 1998, BMJ.