It can take years for humans to solve complex scientific problems. With AI, it can take a fraction of the time.

In a sport where tactics, terrain, weather, and timing all merge into one fluid contest, predicting the outcome of a cycling race can seem like guesswork.

A new study presents a machine learning model that accurately predicts the compressive strength of high-strength concrete, ...

Neural-XGBoost: A Hybrid Approach for Disaster Prediction and Management Using Machine Learning Abstract:Effective disaster prediction is essential for disaster management and mitigation.

The disease is known for its strong association with climatic variables, especially excessive rainfall, high humidity, and ...

Singapore researchers have unveiled a powerful new AI tool that can predict whether a liver cancer patient is likely to ...

AI tool predicts liver cancer relapse with 82% accuracy, tackling a disease causing third-highest cancer-related deaths ...

The term dementia is used to describe various debilitating neurological disorders characterized by a progressive loss of ...

Beyond achieving technical excellence, the study underscores the practical utility of explainable AI in flood risk management ...

Because of its superior parallel processing capabilities and capacity to handle complicated non-linear interactions, XGBoost can successfully tackle machine learning problems.

XGBoost, a widely-used machine learning algorithm, has been applied across various fields. To develop a high-quality model, federated learning is employed, allowing participants to keep their data ...

Subsequently, machine learning based on the 2109 candidate proteins was constructed to screen the most valuable variables. Among the four machine learning algorithms, the accuracy of SVM and XGBoost ...