Introduction In 2006, a federal US court found several major tobacco companies guilty of violating civil racketeering laws ...
Introduction Lung-function outcomes among preterm-born children referred for pulmonology care are highly heterogeneous, and ...
Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...
ABSTRACT: Automatic detection of cognitive distortions from short written text could support large-scale mental-health screening and digital cognitive-behavioural therapy (CBT). Many recent approaches ...
Multimorbidity is associated with adverse outcomes among older adult surgical patients, yet its role in postoperative delirium (POD) remains unclear. In the present study, we hypothesized that ...
Background Despite global efforts to improve nutrition, young women aged 15–24 years in low-income and middle-income countries (LMICs) face persistent dual burdens of malnutrition, marked by high ...
Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
Abstract: The classification problem represents a funda-mental challenge in machine learning, with logistic regression serving as a traditional yet widely utilized method across various scientific ...
The lifetime behaviour of loans is notoriously difficult to model, which can compromise a bank's financial reserves against future losses, if modelled poorly. Therefore, we present a data-driven ...
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