Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Objective: Urinary tract infection (UTI) is a common childhood infectious disease. Accurate prediction of UTI risk in febrile children enables timely intervention and helps avoid long-term ...

Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level ...

This research project conducts a comprehensive comparative study of Random Forest and Gradient-Boosted Trees (XGBoost, CatBoost, and LightGBM) for predicting Indonesian public university tuition fees ...

Treasury PS Chris Kiptoo and other stakeholders during tree planting in Kaptagat forest, Elgeyo Marakwet, on August 21, 2024. [File, Standard] Fifteen years ago, a group of environmental enthusiasts, ...

A team from the Institute for Advanced Study, Emory University in the US, and the Weizmann Institute of Science, Israel, has developed a new mathematical framework to understand how humans store ...

Abstract: Random forests (RF) is an ensemble classification approach, which is easy to use and is helpful to avoid over-fitting. However, in the complex data environment, its prediction accuracy could ...

ABSTRACT: This study proposes a hybrid modeling approach that integrates a Physics Informed Neural Network (PINN) and a long short-term memory (LSTM) network to predict river water temperature in a ...

ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...