The American Journal of Managed Care

Machine Learning May Enable Earlier Detection of CKD Risk Factors

Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

Machine learning for machines This tyre factory’s efficiency soars

Sensors, computer vision models, and artificial intelligence have combined to help CEAT Tyres’ Chennai factory reduce defects, waste and energy use, a.
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Hespress on MSN

Study shows sharp oasis decline in southeastern Morocco’s Ternata over the past 40 years

A group of eight researchers has pointed to a steady decline in the Ternata Oasis, southeastern Morocco, over the past 40 ...
IEEE

Neural-XGBoost: A Hybrid Approach for Disaster Prediction and Management Using Machine Learning

Abstract: Effective disaster prediction is essential for disaster management and mitigation. This study addresses a multi-classification problem and proposes the Neural-XGBoost disaster prediction ...
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

Forecasting Bank ROE with Gradient Boosting: A Machine Learning Approach

Abstract: Return on Equity (ROE) is a critical indicator of a firm's profitability, influenced by various operational, financial, and external factors. Traditional linear models often fail to capture ...