These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
344 related articles for article (PubMed ID: 28754093)
21. A comparison of time to event analysis methods, using weight status and breast cancer as a case study. Aivaliotis G; Palczewski J; Atkinson R; Cade JE; Morris MA Sci Rep; 2021 Jul; 11(1):14058. PubMed ID: 34234154 [TBL] [Abstract][Full Text] [Related]
22. Personalized Risk Prediction in Clinical Oncology Research: Applications and Practical Issues Using Survival Trees and Random Forests. Hu C; Steingrimsson JA J Biopharm Stat; 2018; 28(2):333-349. PubMed ID: 29048993 [TBL] [Abstract][Full Text] [Related]
23. Joint modelling of repeated transitions in follow-up data--a case study on breast cancer data. Genser B; Wernecke KD Biom J; 2005 Jun; 47(3):388-401. PubMed ID: 16053262 [TBL] [Abstract][Full Text] [Related]
24. Survival forests for data with dependent censoring. Moradian H; Larocque D; Bellavance F Stat Methods Med Res; 2019 Feb; 28(2):445-461. PubMed ID: 28835170 [TBL] [Abstract][Full Text] [Related]
25. Mechanistic spatio-temporal point process models for marked point processes, with a view to forest stand data. Møller J; Ghorbani M; Rubak E Biometrics; 2016 Sep; 72(3):687-96. PubMed ID: 26689438 [TBL] [Abstract][Full Text] [Related]
26. Practical aspects of gene regulatory inference via conditional inference forests from expression data. Bessonov K; Van Steen K Genet Epidemiol; 2016 Dec; 40(8):767-778. PubMed ID: 27870152 [TBL] [Abstract][Full Text] [Related]
27. Random survival forests for dynamic predictions of a time-to-event outcome using a longitudinal biomarker. Pickett KL; Suresh K; Campbell KR; Davis S; Juarez-Colunga E BMC Med Res Methodol; 2021 Oct; 21(1):216. PubMed ID: 34657597 [TBL] [Abstract][Full Text] [Related]
28. Using conditional inference forests to identify the factors affecting crash severity on arterial corridors. Das A; Abdel-Aty M; Pande A J Safety Res; 2009; 40(4):317-27. PubMed ID: 19778656 [TBL] [Abstract][Full Text] [Related]
29. Trees and splines in survival analysis. Intrator O; Kooperberg C Stat Methods Med Res; 1995 Sep; 4(3):237-61. PubMed ID: 8548105 [TBL] [Abstract][Full Text] [Related]
30. Identifying important risk factors for survival in patient with systolic heart failure using random survival forests. Hsich E; Gorodeski EZ; Blackstone EH; Ishwaran H; Lauer MS Circ Cardiovasc Qual Outcomes; 2011 Jan; 4(1):39-45. PubMed ID: 21098782 [TBL] [Abstract][Full Text] [Related]
31. Performance of statistical methods for analysing survival data in the presence of non-random compliance. Odondi L; McNamee R Stat Med; 2010 Dec; 29(29):2994-3003. PubMed ID: 20963732 [TBL] [Abstract][Full Text] [Related]
32. Simulating survival data with predefined censoring rates for proportional hazards models. Wan F Stat Med; 2017 Feb; 36(5):838-854. PubMed ID: 27873333 [TBL] [Abstract][Full Text] [Related]
33. Time-dependent covariates in the proportional subdistribution hazards model for competing risks. Beyersmann J; Schumacher M Biostatistics; 2008 Oct; 9(4):765-76. PubMed ID: 18434297 [TBL] [Abstract][Full Text] [Related]
34. Tree-based models for survival data with competing risks. Kretowska M Comput Methods Programs Biomed; 2018 Jun; 159():185-198. PubMed ID: 29650312 [TBL] [Abstract][Full Text] [Related]
35. Optimal Tuning of Random Survival Forest Hyperparameter with an Application to Liver Disease. Dauda KA Malays J Med Sci; 2022 Dec; 29(6):67-76. PubMed ID: 36818901 [TBL] [Abstract][Full Text] [Related]
36. Bayesian random-effects threshold regression with application to survival data with nonproportional hazards. Pennell ML; Whitmore GA; Ting Lee ML Biostatistics; 2010 Jan; 11(1):111-26. PubMed ID: 19828558 [TBL] [Abstract][Full Text] [Related]
37. A Comparison Study of Machine Learning (Random Survival Forest) and Classic Statistic (Cox Proportional Hazards) for Predicting Progression in High-Grade Glioma after Proton and Carbon Ion Radiotherapy. Qiu X; Gao J; Yang J; Hu J; Hu W; Kong L; Lu JJ Front Oncol; 2020; 10():551420. PubMed ID: 33194609 [TBL] [Abstract][Full Text] [Related]
38. Comparison of algorithms to generate event times conditional on time-dependent covariates. Sylvestre MP; Abrahamowicz M Stat Med; 2008 Jun; 27(14):2618-34. PubMed ID: 17918753 [TBL] [Abstract][Full Text] [Related]
39. Model-based approaches to analysing incomplete longitudinal and failure time data. Hogan JW; Laird NM Stat Med; 1997 Jan 15-Feb 15; 16(1-3):259-72. PubMed ID: 9004396 [TBL] [Abstract][Full Text] [Related]
40. Association between split selection instability and predictive error in survival trees. Radespiel-Tröger M; Gefeller O; Rabenstein T; Hothorn T Methods Inf Med; 2006; 45(5):548-56. PubMed ID: 17019510 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]