Blood loss severity prediction using game theoretic based feature selection

2014 IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2014

Volumn , Issue , 2014, Pages 776-780

  Razi, Abolfazl ^a   Afghah, Fatemeh ^b   Belle, Ashwin ^c   Ward, Kevin ^c   Najarian, Kayvan ^c  

^a Duke University   (United States)

^b NORTH CAROLINA A AND T STATE UNIVERSITY   (United States)

^c UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GAME THEORY; PATIENT TREATMENT; SIGNAL PROCESSING;

CLASSIFICATION METHODS; FEATURE SELECTION ALGORITHM; FEATURE SELECTION METHODS; PHYSIOLOGICAL SIGNALS; PREDICTION ACCURACY; SIGNAL PROCESSING TECHNIQUE; STATE OF THE ART; UNSOLVED PROBLEMS;

FORECASTING;

EID: 84906877221     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BHI.2014.6864479     Document Type: Conference Paper

References (30)

1. P. Teixeira, K. Inaba, P. Hadjizacharia, A. Brown, R. T. Browder, T. T. Noguchi, and D. Demetriades, "Preventable or potentially preventable mortality at a mature trauma center," J Trauma, vol. 63, pp. 1338-1346, 2007. [Online]. Available: http://www.nejm.org/doi/full/10.1056/NEJMoa0804748
2. J. F. Kelly, A. E. Ritenour, D. F. McLaughlin, K. A. Bagg, A. N. Apodaca, C. T. Mallak, L. Pearse, M. M. Lawnick, H. R. Champion, C. E. Wade, and J. B. Holcomb, "Injury severity and causes of death from operation iraqi freedom and operation enduring freedom: 2003-2004 versus 2006," J Trauma, vol. 64, pp. 521-526, 2008
3. M. H. Weil, L. Becker, T. Budinger, K. Kern, G. Nichol, I. Shechter, R. Traystman, H. Wiedemann, R. Wise, M. Weisfeldt, and G. Sopko, "Post resuscitative and initial utility in life saving efforts (pulse): A workshop executive summary," in Resuscitation, vol. 50, 2001, pp. 23-35
4. H. B. Alam, D. Burris, and J. A. DaCorta, "Hemorrhage control in the battlefield: Role of new hemostatic agents," Military Medicine, vol. 170, pp. 63-69, 2005
5. V. Convertino, K. Ryan, C. Rickards, J. Salinas, J. McManus, W. Cooke, and J. Holcomb, "Physiological and medical monitoring for en route care of combat casualties," Journal of Trauma, vol. 64, pp. 342-353, 2008
6. S.-Y. Ji, A. Belle, K. R. Ward, K. L. Ryan, C. A. Rickards, V. A. Convertino, and K. Najarian, "Heart rate variability analysis during central hypovolemia using wavelet transformation," Journal of Clinical Monitoring and Computing, pp. 1-14, 2013
7. A. A. R. Bsoul, S. Ji, K. Ward, K. Ryan, C. Rickard, V. Convertino, and K. Najarian, "Prediction of severity of blood volume loss using features based on p, t and qrs waves," in 2009 American Heart Association (AHA) Resuscitation Science Symposium, 2009
8. S. Ji, A. Bsoul, K. Ward, K. Ryan, C. Rickard, V. Convertino, and K. Najarian, "Incorporating physiological signals to blood loss prediction based on discrete wavelet transformation," in 2009 American Heart Association (AHA) Resuscitation Science Symposium, 2009
9. I. Guyon and A. Elisseeff, "An introduction to variable and feature selection," J. Mach. Learn. Res., vol. 3, pp. 1157-1182, March 2003. Available: http://dl.acm.org/citation.cfm?id=944919.944968
10. Y. Saeys, I. n. Inza, and P. Larrañaga, "A review of feature selection techniques in bioinformatics," Bioinformatics, vol. 23, no. 19, pp. 2507-2517, Sep. 2007
11. C. Lazar, J. Taminau, S. Meganck, D. Steenhoff, A. Coletta, C. Molter, V. de Schaetzen, R. Duque, H. Bersini, and A. Nowe, "A survey on filter techniques for feature selection in gene expression microarray analysis," Computational Biology and Bioinformatics, IEEE/ACM Transactions on, vol. 9, no. 4, pp. 1106-1119, 2012
12. M. E. Tipping, "Sparse bayesian learning and the relevance vector machine," J. Mach. Learn. Res., vol. 1, pp. 211-244, Sep. 2001. Available: http://dx.doi.org/10.1162/15324430152748236
13. Y. Mohsenzadeh, H. Sheikhzadeh, A. Reza, N. Bathaee, and M. Kalayeh, "The relevance sample-feature machine: A sparse bayesian learning approach to joint feature-sample selection," Cybernetics, IEEE Transactions on, vol. 43, no. 6, pp. 2241-2254, 2013
14. J. Huang, Y. Cai, and X. Xu, "A wrapper for feature selection based on mutual information," in Pattern Recognition, 2006. ICPR 2006. 18th International Conference on, vol. 2, 2006, pp. 618-621
15. R. Kohavi and G. John, "Wrappers for feature subset selection," Artificial Intelligence, vol. 97, pp. 273-324, 1997
16. H. Peng, F. Long, and C. Ding, "Feature selection based on mutual information criteria of max-dependency, max-relevance, and minredundancy," Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 27, no. 8, pp. 1226-1238, 2005
17. J. Fan, R. Samworth, and Y. Wu, "Ultrahigh dimensional feature selection: Beyond the linear model," Journal of Machine Learning Research, vol. 10, pp. 2013-2038, 2009
18. D. M. Witten and R. Tibshirani, "Penalized classification using fisher's linear discriminant," Journal of the Royal Statistical Society: Series B (Statistical Methodology), 10 2011
19. M. T. W. Irina Gaynanova, James G. Booth, "Supervised classification using sparse fisher's lda," arXiv:1301.4976
20. Z. Nenadic, "Information discriminant analysis: Feature extraction with an information-theoretic objective," Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 29, no. 8, pp. 1394-1407, 2007
21. M. Chen, W. R. Carson, M. R. D. Rodrigues, L. Carin, and A. R. Calderbank, "Communications inspired linear discriminant analysis." in ICML. icml.cc / Omnipress, 2012
22. T. Suzuki, M. Sugiyama, and T. Tanaka, "Mutual information approximation via maximum likelihood estimation of density ratio," in Information Theory, 2009. ISIT 2009. IEEE International Symposium on, 2009, pp. 463-467
23. W. H. Cooke, K. L. Ryan, and V. A. Convertino, "Lower body negative pressure as a model to study progression to acute hemorrhagic shock in humans," J. Appl. Physiol., vol. 96, pp. 1249-1261, 2004
24. Y. Luo, "The severity of stages estimation during hemorrhage using error correcting output codes method," VCU digital archives, Virginia Commonwealth University, Richmond, Virginia, 2012
25. A. Bsoul, S. Ji, K. Ward, and K. Najarian, "Detection of p, qrs, and t components of ecg using wavelet transformation," in 2009 IEEE/ICME International Conference on Complex Medical Engineering (CME2009), 2009
26. X. Sun, Y. Liu, J. Li, J. Zhu, H. Chen, and X. Liu, "Feature evaluation and selection with cooperative game theory," Pattern Recogn., vol. 45, no. 8, pp. 2992-3002, Aug. 2012. [Online]. Available: http://dx.doi.org/10.1016/j.patcog.2012.02.001
27. G. Cohen, S. Dror and G. Ruppin, "Feature selection via coalitional game theory," Neural Computation, vol. 19, no. 7, pp. 1939-1961, 2007
28. L. S. Shapley, "A value for n-person games," H. W. Kuhn, and A. W. Tucker (Eds.), Contributions to the theory of games, vol. 2, pp. 307-317, 1953
29. A. Keinan, B. Sandbank, C. Hilgetag, I. Meilijson, and E. Ruppin, "Axiomatic scalable neurocontroller analysis via the shapley value," Artificial Life, vol. 12, pp. 333-352, 2006
30. K. M. Kaufman, A. and E. Ruppin, "Multi-knockout genetic network analysis: The rad6 example," in IEEE Computational Systems Bioinformatics Conference (CSB04), 2004, pp. 332-340.