In light of the growing burden CKD (Chronic Kidney Disease), it is particular importance to us create disease prediction models that will assist healthcare providers in identifying cases individual risk and integrate risk-based care for progress management. The objective was develop validate a new pragmatic ESKD (End-Stage Disease) utilizing Cox (Cox proportional hazard) ML (machine learning).

The aim of this study was to identify risk factors for culling, sales and deaths in intensively managed dairy goat herds in New Zealand. A data set provided by the New Zealand Dairy Goat Cooperative (n = 13,197 does) was analyzed using a Cox proportional hazard model. The outcome of interest was length of productive life (LPL), defined as the number of days from the date of second kidding to th...

background dietary factors such as intake of minerals may play a role in the etiology of esophageal cancer. although it has been hypothesized that manganese can affect the risk of some types ofcancer, its role in esophageal cancer is unknown. the objective of this study was to investigate the association between intakes of manganese with esophageal cancer in golestan cohort study. materials and...

Existing models for predicting mortality based on traditional Cox proportional hazard approach (CPH) often have low prediction accuracy. This paper aims to develop a clinical risk model with good accuracy for predicting 1-year mortality in cardiac arrhythmias patients using random survival forest (RSF), a robust approach for survival analysis. 10,488 cardiac arrhythmias patients available in th...

INTRODUCTION We used agent-based simulation to examine the problem of time-varying confounding when estimating the effect of an adverse event on hospital length of stay. Conventional analytic methods were compared with inverse probability weighting (IPW). METHODS A cohort of hospitalized patients, at risk for experiencing an adverse event, was simulated. Synthetic individuals were assigned a ...