Download PDF More Formats on IMF eLibrary Order a Print Copy Create Citation Model selection and forecasting in stress tests can be facilitated using machine learning techniques. These techniques have ...

In linear regression with functional predictors and scalar responses, it may be advantageous, particularly if the function is thought to contain features at many scales, to restrict the coefficient ...

急性胰腺炎（AP）致死率高且缺乏精准预后工具。本研究针对 AP 患者 30 天 mortality 风险，利用 LASSO logistic regression 筛选出年龄、APTT、DBIL 等 6 个独立预测因子，构建 nomogram 模型（AUC=0.862），经 DCA 验证具临床价值，为早期风险分层提供新工具。 急性胰腺炎（Acute ...

• A prediction model for assessing the risk of coagulation disorders after coronary artery bypass grafting (CABG) was developed and demonstrated good prediction performance in elderly individuals, ...

The prediction model was developed in a primary cohort that consisted of 326 patients with clinicopathologically confirmed CRC, and data was gathered from January 2007 to April 2010. Radiomic features ...

We introduce a fast stepwise regression method, called the orthogonal greedy algorithm (OGA), that selects input variables to enter a p-dimensional linear regression model (with p ≫ n, the sample size ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...