Researchers found that the extreme gradient boosting (XGBoost) predictor could more accurately predict rheumatoid arthritis (RA) relapse than logistic regression and random forest. When evaluating ...

Mangrove ecosystems, vital for biodiversity and climate change mitigation, face challenges in monitoring and conservation due to their complex species composition. A new study introduces an AI-driven ...

Researchers have developed a novel AI-driven framework using the XGBoost algorithm to accurately evaluate the skid resistance of asphalt pavements under various conditions. Published in Smart ...

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

Scientists at the Delft University of Technology in the Netherlands have developed a machine-learning (ML) technique to predict power yields in rooftop PV system. They claim it can predict electricity ...

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

An international research team has utilized a machine learning algorithm known as XGBoost (eXtreme Gradient Boosting) to predict PV adoption among homeowners. This algorithm consists of a distributed ...

A publicly available AI tool correctly predicted approximately twice as many children with acute lymphoblastic leukemia who would relapse as three expert clinicians.XGBoost, a boosting algorithm, had ...

By Hugo Francisco de Souza A new study shows that gut microbiome signatures, analyzed through advanced machine learning, can help identify individuals with more severe insulin resistance, offering ...