Classifying readmissions to a cardiac intensive care unit

[1]  Onur Seref,et al.  Weighted relaxed support vector machines , 2014, Annals of Operations Research.

[2]  Vaibhav Rajan,et al.  Classification with imbalance: A similarity-based method for predicting respiratory failure , 2015, 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

[3]  Cemil Kuzey,et al.  Analyzing initial public offerings' short-term performance using decision trees and SVMs , 2015, Decis. Support Syst..

[4]  Erkam Güresen,et al.  Developing an early warning system to predict currency crises , 2014, Eur. J. Oper. Res..

[5]  María N. Moreno García,et al.  Machine Learning Methods for Mortality Prediction of Polytraumatized Patients in Intensive Care Units - Dealing with Imbalanced and High-Dimensional Data , 2014, IDEAL.

[6]  Karen Page,et al.  Intensive care readmission: a contemporary review of the literature. , 2014, Intensive & critical care nursing.

[7]  Selim Zaim,et al.  A machine learning-based usability evaluation method for eLearning systems , 2013, Decis. Support Syst..

[8]  Uzay Kaymak,et al.  Predicting intensive care unit readmissions using probabilistic fuzzy systems , 2013, 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[9]  Ankur Teredesai,et al.  Predicting Risk-of-Readmission for Congestive Heart Failure Patients: A Multi-Layer Approach , 2013, ArXiv.

[10]  Samir M Fakhry,et al.  Intensive care unit bounce back in trauma patients: An analysis of unplanned returns to the intensive care unit , 2013, The journal of trauma and acute care surgery.

[11]  Yazan F. Roumani,et al.  Classifying highly imbalanced ICU data , 2013, Health care management science.

[12]  João Miguel da Costa Sousa,et al.  Data mining using clinical physiology at discharge to predict ICU readmissions , 2012, Expert Syst. Appl..

[13]  Panos M. Pardalos,et al.  Robust Data Mining , 2012 .

[14]  Jean-François Timsit,et al.  A model to predict short-term death or readmission after intensive care unit discharge. , 2012, Journal of critical care.

[15]  Francisco Herrera,et al.  Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics , 2012, Expert Syst. Appl..

[16]  Jens Myrup Pedersen,et al.  A method for classification of network traffic based on C5.0 Machine Learning Algorithm , 2012, 2012 International Conference on Computing, Networking and Communications (ICNC).

[17]  P. Stow,et al.  Factors associated with increased risk of readmission to intensive care in Australia , 2011, Intensive Care Medicine.

[18]  Florin Gorunescu,et al.  Data Mining - Concepts, Models and Techniques , 2011, Intelligent Systems Reference Library.

[19]  Rodica Potolea,et al.  Imbalanced Classification Problems: Systematic Study, Issues and Best Practices , 2011, ICEIS.

[20]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[21]  Qinghua Hu,et al.  A novel measure for evaluating classifiers , 2010, Expert Syst. Appl..

[22]  R. Jarden,et al.  Improving safety and documentation in intrahospital transport: development of an intrahospital transport tool for critically ill patients. , 2010, Intensive & critical care nursing.

[23]  Wei Jiang,et al.  Adjusted support vector machines based on a new loss function , 2010, Ann. Oper. Res..

[24]  Yanchun Zhang,et al.  Toward breast cancer survivability prediction models through improving training space , 2009, Expert Syst. Appl..

[25]  Yue-Shi Lee,et al.  Cluster-based under-sampling approaches for imbalanced data distributions , 2009, Expert Syst. Appl..

[26]  H. Thaler,et al.  Review of A Large Clinical Series: Intrahospital Transport of Critically Ill Patients: Outcomes, Timing, and Patterns , 2009, Journal of intensive care medicine.

[27]  Chih-Jen Lin,et al.  LIBLINEAR: A Library for Large Linear Classification , 2008, J. Mach. Learn. Res..

[28]  B. Cuthbertson,et al.  Predicting death and readmission after intensive care discharge. , 2008, British journal of anaesthesia.

[29]  Philip S. Yu,et al.  Top 10 algorithms in data mining , 2007, Knowledge and Information Systems.

[30]  Susannah L Rose,et al.  Factors influencing length of stay in the intensive care unit. , 2006, American journal of critical care : an official publication, American Association of Critical-Care Nurses.

[31]  Peter J Pronovost,et al.  Intensive care unit physician staffing: Financial modeling of the Leapfrog standard* , 2004, Critical care medicine.

[32]  Nitesh V. Chawla,et al.  Editorial: special issue on learning from imbalanced data sets , 2004, SKDD.

[33]  Albert W. Wu,et al.  Incidents relating to the intra-hospital transfer of critically ill patients , 2004, Intensive Care Medicine.

[34]  Eric R. Ziegel,et al.  The Elements of Statistical Learning , 2003, Technometrics.

[35]  D. Edwards.  Data Mining: Concepts, Models, Methods, and Algorithms , 2003 .

[36]  Nathalie Japkowicz,et al.  The class imbalance problem: A systematic study , 2002, Intell. Data Anal..

[37]  Kai Ming Ting,et al.  An Instance-weighting Method to Induce Cost-sensitive Trees , 2001 .

[38]  P M Reilly,et al.  The traveling intensive care unit patient. Road trips. , 2000, The Surgical clinics of North America.

[39]  A J Rotondi,et al.  Are readmissions to the intensive care unit a useful measure of hospital performance? , 1999, Medical care.

[40]  D. Kleinbaum,et al.  Applied Regression Analysis and Other Multivariate Methods , 1978 .

[41]  C. Schorr,et al.  Fishing for answers to avoid intensive care unit readmissions: are we reeling in a "catch 22"?. , 2012, Critical care medicine.

[42]  M. Kurt,et al.  Predictors and outcome of ICU readmission after cardiac surgery. , 2009, The Thoracic and cardiovascular surgeon.

[43]  Han Tong Loh,et al.  Imbalanced text classification: A term weighting approach , 2009, Expert Syst. Appl..

[44]  Ralescu Anca,et al.  ISSUES IN MINING IMBALANCED DATA SETS - A REVIEW PAPER , 2005 .

[45]  Nitesh V. Chawla,et al.  SMOTE: Synthetic Minority Over-sampling Technique , 2002, J. Artif. Intell. Res..

[46]  D. Kleinbaum,et al.  Applied regression analysis and other multivariable methods, 3rd ed. , 1998 .