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Proportional Hazards Models

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Optimal adjuvant endocrine treatment of ER+/HER2+ breast cancer patients by age at diagnosis: A population-based cohort study.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Prior randomised controlled trials on adjuvant hormonal therapy included HER2 patients; however, a differential effect of aromatase inhibitors (AIs) versus tamoxifen (TAM) may have been missed in ER+/HER2+ patients that comprise 7-15% of ...

Estimating causal effects for survival (time-to-event) outcomes by combining classification tree analysis and propensity score weighting.

Journal of evaluation in clinical practice
RATIONALE, AIMS AND OBJECTIVES: A common approach to assessing treatment effects in nonrandomized studies with time-to-event outcomes is to estimate propensity scores and compute weights using logistic regression, test for covariate balance, and then...

A new semi-supervised learning model combined with Cox and SP-AFT models in cancer survival analysis.

Scientific reports
Gene selection is an attractive and important task in cancer survival analysis. Most existing supervised learning methods can only use the labeled biological data, while the censored data (weakly labeled data) far more than the labeled data are ignor...

Deep Learning-Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer.

Clinical cancer research : an official journal of the American Association for Cancer Research
Identifying robust survival subgroups of hepatocellular carcinoma (HCC) will significantly improve patient care. Currently, endeavor of integrating multi-omics data to explicitly predict HCC survival from multiple patient cohorts is lacking. To fill ...

A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study.

Scientific reports
Accurate prediction of graft survival after kidney transplant is limited by the complexity and heterogeneity of risk factors influencing allograft survival. In this study, we applied machine learning methods, in combination with survival statistics, ...

Modeling time-to-event (survival) data using classification tree analysis.

Journal of evaluation in clinical practice
RATIONALE, AIMS, AND OBJECTIVES: Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (cal...

DCE-MRI prediction of survival time for patients with glioblastoma multiforme: using an adaptive neuro-fuzzy-based model and nested model selection technique.

NMR in biomedicine
This pilot study investigates the construction of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the prediction of the survival time of patients with glioblastoma multiforme (GBM). ANFIS is trained by the pharmacokinetic (PK) parameters estimat...

Predictive model for 5-year mortality after breast cancer surgery in Taiwan residents.

Chinese journal of cancer
BACKGROUND: Few studies of breast cancer surgery outcomes have used longitudinal data for more than 2 years. This study aimed to validate the use of the artificial neural network (ANN) model to predict the 5-year mortality of breast cancer patients a...