Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
IEEE

Vegetable Sales Forecasting Based on XGBOOST Algorithm and Random Forest

Abstract: This paper explores the forecasting of vegetable sales and the optimization of procurement strategies using the XGBOOST algorithm and random forest methodology. The study begins by utilizing ...
IEEE

Predicting Agricultural Waste Biogas Potential in Anaerobic Digestion Using XGBoost Algorithm

Abstract: The rising need for renewable energy has stimulated interest in agricultural waste as a medium for biogas generation via anaerobic digestion. This research uses the XGBoost algorithm to ...
The Lancet

Identification and validation of an explainable early-stage chronic kidney disease prediction model: a multicenter retrospective study

aSchool of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine, Nanjing, China bJiangsu Province Engineering Research Center of TCM Intelligence Health Service, ...
Frontiers

Web-based cardiovascular disease risk prediction using machine learning

Cardiovascular disease (CVD) remains the foremost contributor to global illness and death, underscoring the critical need for effective tools that can predict risk at early stages to support ...