Researchers developed a machine learning model that could identify children in the ED who were at risk for developing sepsis ...

An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...

A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.

A new research paper shows the approach performs significantly better than the random-walk forecasting method.

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

While AI models may exhibit addiction-like behaviors, the technology is also proving to be a powerful ally in combating real ...

A research team has developed a new way to measure and predict how plant leaves scatter and reflect light, revealing that leaf optical behavior can be accurately inferred from measurable phenotypic ...

Of the ML models, the XGBoost had the best performance, with an AUC of 0.941 on the training set and an AUC of 0.775 on the internal validation set. The combination of clinical data with machine ...

ABSTRACT: The surge of digital data in tourism, finance and consumer markets demands predictive models capable of handling volatility, nonlinear dynamics, and long-term dependencies, where traditional ...

Background: Standard CVD risk calculators assume linear relationships among risk factors. ML methods (gradient boosting, random forests, neural networks, support vector machines) capture nonlinear ...