Int J Performability Eng ›› 2023, Vol. 19 ›› Issue (2): 85-93.doi: 10.23940/ijpe.23.02.p1.8593
Liwei Chena, Jianhao Ana,*, Mingxin Dub, and Kai Sua
| 1. Cox D.R.Regression models and life-tables.
2. Calvet X., Bruix J., Ginés P., Bru C., Sole M., Vilana R., andRodés J.Prognostic factors of hepatocellular carcinoma in the west: a multivariate analysis in 206 patients.
3. Yeh C.N., Chen M.F., Lee W.C., andJeng L.B.Prognostic factors of hepatic resection for hepatocellular carcinoma with cirrhosis: univariate and multivariate analysis.
4. Wu T.H., Yu M.C., Chan K.M., Lee C.F., Chen T.C., Chang H.C., Chou H.S., Wu T.J., Eldeen F.Z., Chen M.F., andLee W.C.Prognostic effect of steatosis on hepatocellular carcinoma patients after liver resection.
5. Ho C.M., Wu C.Y., Lee P.H., Lai H.S., Ho M.C., Wu Y.M., andHu R.H.Analysis of the risk factors of untransplantable recurrence after primary curative resection for patients with hepatocellular carcinoma.
6. Si S., Zhao J., Cai Z., andDui H.Recent advances in system reliability optimization driven by importance measures.
7. Birnbaum Z.W.
8. Cheok M.C., Parry G.W., andSherry R.R.Use of importance measures in risk-informed regulatory applications.
9. Griffith W.S.Multistate reliability models.
10. Wu T.H., Yu M.C., Chan K.M., Lee C.F., Chen T.C., Chang H.C., Chou H.S., Wu T.J., Eldeen F.Z., Chen M.F., andLee W.C.Prognostic effect of steatosis on hepatocellular carcinoma patients after liver resection.
11. Ramirez-Marquez, J.E., and Coit, D.W. Composite importance measures for multi-state systems with multi-state components.
12. Ramirez-Marquez, J.E. and Coit, D.W. Multi-state component criticality analysis for reliability improvement in multi-state systems.
13. Zio, E., Marella, M. and Podofillini, L.Importance measures-based prioritization for improving the performance of multi-state systems: application to the railway industry.
14. Natvig B., Eide K.A., Gåsemyr J., Huseby A.B., andIsaksen S.L.Simulation based analysis and an application to an offshore oil and gas production system of the Natvig measures of component importance in repairable systems.
15. Peng H., Coit D.W., andFeng Q.Component reliability criticality or importance measures for systems with degrading components.
16. Gevaert O., Smet F.D., Timmerman D., Moreau Y., andMoor B.D.Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks.
17. Si S., Zhao J., Cai Z., andDui H.Recent advances in system reliability optimization driven by importance measures.
18. Si S.B., Liu G.M., Cai Z.Q., andXia P.Using Bayesian networks to built a diagnosis and prognosis model for breast cancer. In
19. Wang, C.Y. and Li, S. Clinical characteristics and prognosis of2887 patients with hepatocellular carcinoma: a single center 14 years experience from China.
20. Scutari M.Bayesian network models for incomplete and dynamic data.
21. Duda R.O., Hart P.E., andStork D.G.
22. Friedman, N., Geiger, D. and Goldszmidt, M.Bayesian network classifiers.
23. Vasseur, D. and Llory, M.International survey on PSA figures of merit.
24. Marcot, B.G. and Penman, T.D.Advances in Bayesian network modelling: Integration of modelling technologies.
25. Fawcett T.An introduction to ROC analysis.
26. Krstinić D., Braović M., Šerić L., andBožić-Štulić, D. Multi-label classifier performance evaluation with confusion matrix.
27. Alonso, R. and Pardo, M.C.Assessing influence on the estimated coefficients efficiency in a Cox regression model.
28. Heller, G. and Simonoff, J.S.Prediction in censored survival data: a comparison of the proportional hazards and linear regression models.
29. Reid, N. and Cox, D.R.
30. Fieller E.C., Hartley H.O., andPearson E.S.Tests for rank correlation coefficients. I.
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