Author’s response to reviews Title: Predictors for independent external validation of cardiovascular risk clinical prediction rules: Cox proportional hazards regression analyses Authors:

Predictors for independent external validation of cardiovascular risk clinical prediction rules: Cox proportional hazards regression analyses

Background: Clinical prediction rules (CPRs) should be externally validated by independent researchers. Although there are many cardiovascular CPRs, most have not been externally validated. It is not known why some CPRs are externally validated by independent researchers and others are not. Methods: We analyzed cardiovascular risk CPRs included in a systematic review. Independent external valid...

Author’s response to reviews Title: External validation, update and development of prediction models for pre-eclampsia using an Individual Participant Data (IPD) meta-analysis: the International Prediction of Pregnancy Complication Network (IPPIC Pre-eclampsia) protocol Authors:

Hierarchical Alpha-cut Fuzzy C-means, Fuzzy ARTMAP and Cox Regression Model for Customer Churn Prediction

As customers are the main asset of any organization, customer churn management is becoming a major task for organizations to retain their valuable customers. In the previous studies, the applicability and efficiency of hierarchical data mining techniques for churn prediction by combining two or more techniques have been proved to provide better performances than many single techniques over a nu...

Computer programs to estimate overoptimism in measures of discrimination for predicting the risk of cardiovascular diseases.

BACKGROUND Development of chronic disease risk prediction models has become a growing area of research in recent years. The internal validity of such models is sometimes lower than estimated from the development sample. Overfitting or overoptimism of the developed model and/or differences between the samples are likely causes for this. For modelling of an uncommon outcome, bootstrapping for ove...

Comparison of Artificial Neural Networks and Cox Regression Models in Prediction of Kidney Transplant Survival

Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...