The researchers argue that their findings, published in Scientific Reports, could help clinicians anticipate which patients ...

Objective To develop prediction models for short-term outcomes following a first acute myocardial infarction (AMI) event (index) or for past AMI events (prevalent) in a national primary care cohort.

In epidemiological studies, continuous covariates often are measured with error and categorical covariates often are misclassified. Using the logistic regression ...

Dr. James McCaffrey of Microsoft Research demonstrates applying the L-BFGS optimization algorithm to the ML logistic regression technique for binary classification -- predicting one of two possible ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

Background: Patients with liver abscess are at high risk of developing invasive K. pneumonia liver abscess syndrome (IKPLAS), which can worsen survival and quality of life. Early identification of ...

This paper illustrates the validation of a mortgage prepayment forecasting model using a dynamic bivariate-choice regression method. The results demonstrate that the dynamic bivariate-choice ...