Censored time trees™ for predicting time to PSA recurrence

Proceedings - ICMLA 2005: Fourth International Conference on Machine Learning and Applications

Volumn 2005, Issue , 2005, Pages 221-226

  Zubek, Valentina Bayer ^a   Verbel, David ^a   Saidi, Olivier ^a  

^a Aureon Laboratories Inc   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CENSORED TIME TREES; RADICAL PROSTATECTOMY; RECEIVER OPERATING CHARACTERISTIC CURVE; SUPPORT VECTOR REGRESSION;

BIOMEDICAL ENGINEERING; HORMONES; LINEAR PROGRAMMING; MEDICAL COMPUTING; REGRESSION ANALYSIS;

TUMORS;

EID: 33847258395     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLA.2005.14     Document Type: Conference Paper

References (22)

1. L. Breiman, L., J. Friedman, R. Olshen, and C. Stone, "Classification and regression trees", Chapman & Hall/CRC, 1984.
2. M. Kattan, T. Wheeler, and P. Scardino, "Postoperative nomogram for disease recurrence after radical prostatectomy for prostate cancer", Journal of Clinical Oncology, vol. 17, no. 5, 1999, pp. 1499-1507.
3. D. Cox, "Regression models and life tables (with discussion)", Journal of the Royal Statistical Society, B, 74, 1972, pp. 187-220.
4. A. Molinaro, S. Dudoit, and M. van der Laan, "Tree-based multivariate regression and density estimation with right-censored data", U.C. Berkeley, working paper 135, 2003.
5. T. Hothorn, P. Buhlmann, S. Dudoit, A. Molinaro, and M. van der Laan, "Survival Ensembles", U.C. Berkeley, working paper 174, 2005.
6. R. Davis, and J. Anderson, "Exponential survival trees", Statistics in Medicine, vol. 8, 1989, pp. 947-961.
7. M. LeBlanc, and J. Crowley, "Relative risk trees for censored survival data", Biometrics 48, 1992, pp. 411-425.
8. L. Gordon, and R. Olshen, "Tree-structured survival analysis", Cancer treatment reports, vol. 69, no. 10, 1985, pp. 1065-1068.
9. M. Segal, "Regression trees for censored data", Biometrics 44, 1988, pp.35-48.
10. L. Breiman, "Bagging predictors", Machine Learning, vol. 24, no. 2, 1996, pp. 123-140.
11. T. Hothorn, B. Lausen, A. Benner, and M. Radespiel-Troger, "Bagging survival trees", Statistics in Medicine, 23(1), 2004, pp. 77-91.
12. O. Mangasarian, N. Street, and W. Wolberg, "Breast cancer diagnosis and prognosis via linear programming", Operations Research, 43(4), 1995, pp. 570-577.
13. B. Efron, and R. Tibshirani, "An introduction to the bootstrap", Chapman & Hall, New York, 1993.
14. V. Vapnik, "The nature of statistical theory", Springer Verlag, 1995.
15. N. Cristianini, and J. Shawe-Taylor, "An introduction to support vector machines", Cambridge University Press, 2000.
16. A. Smola, and B. Scholkopf, "A tutorial on support vector regression", NeuroCOLT2 Technical Report Series, NC2-TR-1998-030, 1998.
17. L. Yan, D. Verbel, and O. Saidi, "Predicting prostate cancer recurrence via maximizing the concordance index", ACM SIGKDD Conference 2004 Proceedings, pp. 479-485.
18. F. Harrell, R. Califf, and D. Pryor, "Evaluating the yield of medical tests", Journal of American Medical Association, vol. 247, 1982, pp. 2543-2546.
19. F. Provost, and T. Fawcett, "Analysis and visualization of classifier performance: comparison under imprecise class and cost distributions", KDD Conference, 1997.
20. S.H. Park, J. M. Goo, and C. Jo, "Receiver operating characteristic (ROC) curve: practical review for radiologists", Korean Journal of Radiology, 5(1), 2004, pp. 11-18.
21. D. Hand, and R. Till, "A simple generalization of the area under the ROC curve for multiple class classification problems", Machine Learning, 45, 2001, pp. 171-186.
22. J. Hanley, and B. McNeil, "The meaning and use of the area under a Receiver Operating Characteristic (ROC) Curve", Radiology, 143, 1982, pp. 29-36.