Abstract: We propose a soft gradient boosting framework for sequential regression that embeds a learnable linear feature transform within the boosting procedure. At each boosting iteration, we train a ...

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 ...

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

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

ACGRIME is an improved metaheuristic algorithm derived from the original RIME framework. ACGRIME integrates three strategic mechanisms: chaotic initialization, adaptive weighting and Gaussian mutation ...

Please provide your email address to receive an email when new articles are posted on . Early detection and treatment of sepsis can improve outcomes for children. A team of physicians and computer ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

To enjoy bushels of apples, pears, and other favorite fruits, there are a few fruit tree care tips that can enhance your harvest. Keeping your trees healthy will go a long way toward encouraging fruit ...

Having an accurate estimation for Arkansas’ above ground forest biomass has numerous economic and environmental impacts, Dr. Hamdi Zurqani told Talk Business & Politics. The key is to understand how ...

Hamdi Zurqani is a geospatial scientist with the Arkansas Forest Resources Center and the College of Forestry, Agriculture and Natural Resources at the University of Arkansas at Monticello. (U of A ...